diff --git a/.editorconfig b/.editorconfig
index a071a989..94b66ac2 100644
--- a/.editorconfig
+++ b/.editorconfig
@@ -1,26 +1,40 @@
-
-root = true
-
-[*]
-end_of_line = lf
-charset = utf-8
-trim_trailing_whitespace = true
-insert_final_newline = true
-
-[!src/llvm-project]
-indent_style = space
-indent_size = 4
-
-[*.rs]
-max_line_length = 100
-
-[*.md]
-# double whitespace at end of line
-# denotes a line break in Markdown
-trim_trailing_whitespace = false
-
-[*.yml]
-indent_size = 2
-
-[Makefile]
-indent_style = tab
+# EditorConfig is awesome: https://EditorConfig.org
+
+# top-most EditorConfig file
+root = true
+
+[*]
+charset = utf-8
+end_of_line = crlf
+indent_style = space
+indent_size = 4
+insert_final_newline = false
+quote_type = double
+trim_trailing_whitespace = false
+
+[*.{ts,tsx,js,jsx,cjs,mjs}]
+indent_size = 2
+quote_type = single
+
+[*.{json,yaml,yml,toml}]
+indent_size = 2
+
+[*{toml}]
+end_of_line = lf
+indent_size = 2
+
+[*.md]
+insert_final_newline = true
+trim_trailing_whitespace = true
+
+[*.rs]
+indent_size = 4
+
+[*.{html,htm,xml}]
+indent_size = 2
+
+[*.{css,scss,sass,less}]
+indent_size = 2
+trim_trailing_whitespace = true
+insert_final_newline = true
+
diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index b122d1b5..a0033ceb 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -5,17 +5,7 @@ updates:
     schedule:
       interval: monthly
     directories:
-      - /
-      - /concision
-      - /core
-      - /data
-      - /derive
-      - /init
-      - /macros
-      - /neural
-      - /tensor
-      - /utils
-      - /ext
+      - /*
       - /models/*
   - package-ecosystem: devcontainers
     directory: /
diff --git a/.github/workflows/cargo-bench.yml b/.github/workflows/cargo-bench.yml
deleted file mode 100644
index 915db1e3..00000000
--- a/.github/workflows/cargo-bench.yml
+++ /dev/null
@@ -1,52 +0,0 @@
-name: Benchmark
-
-concurrency:
-  cancel-in-progress: false
-  group: ${{ github.workflow }}-${{ github.ref }}
-
-env:
-  CARGO_TERM_COLOR: always
-  RUST_BACKTRACE: full
-
-on:
-  repository_dispatch:
-    types: [ cargo-bench, benchmark ]
-  workflow_dispatch:
-
-permissions:
-  contents: write
-  checks: write
-
-jobs:
-  benchmark:
-    runs-on: ubuntu-latest
-    outputs:
-      digest: ${{ steps.artifacts.outputs.artifact-digest }}
-      id: ${{ steps.artifacts.outputs.artifact-id }}
-      url: ${{ steps.artifacts.outputs.artifact-url }}
-    strategy:
-      fail-fast: false
-      matrix:
-        target: [ x86_64-unknown-linux-gnu ]
-    steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
-      -
-        name: Setup Rust
-        uses: actions-rust-lang/setup-rust-toolchain@v1
-        with:
-          cache-key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
-          target: ${{ matrix.target }}
-      -
-        name: Benchmark the workspace
-        run: cargo bench --locked --verbose --workspace --target ${{ matrix.target }} --features full --
-      -
-        name: Upload the benchmarks
-        id: artifacts
-        uses: actions/upload-artifact@v4
-        with:
-          name: Benchmark Report (${{ github.event.repository.name }})
-          if-no-files-found: error
-          overwrite: true
-          path: target/criterion/
diff --git a/.github/workflows/cargo-clippy.yml b/.github/workflows/cargo-clippy.yml
index ebcad617..244030d5 100644
--- a/.github/workflows/cargo-clippy.yml
+++ b/.github/workflows/cargo-clippy.yml
@@ -6,24 +6,15 @@ concurrency:
 
 on:
   pull_request:
-    branches:
-      - main
-      - $default-branch
-    types:
-      - opened
-      - reopened
-      - synchronize
+    branches: [main, master]
+    types: [edited, opened, ready_for_review, reopened]
   push:
-    branches:
-      - main
-      - $default-branch
-    tags:
-      - v*.*.*
-      - "*-nightly"
+    branches: [main, master]
+    tags: [v*.*.*, "*-nightly"]
   release:
-    types: [ created, edited ]
+    types: [created, edited]
   repository_dispatch:
-    types: [ clippy, cargo-clippy ]
+    types: [clippy, cargo-clippy]
   workflow_dispatch:
 
 jobs:
@@ -35,30 +26,24 @@ jobs:
       security-events: write
       statuses: write
     steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
-      -
-        name: Setup Rust
+      - name: Checkout
+        uses: actions/checkout@v5
+      - name: Setup Rust
         uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
           cache-key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
           components: clippy, rustfmt
           toolchain: nightly
           override: true
-      -
-        name: Setup the for sarif output
+      - name: Setup the for sarif output
         run: cargo install clippy-sarif sarif-fmt
-      -
-        name: Run Clippy
-        run:
-          cargo clippy
+      - name: Run Clippy
+        run: cargo clippy
           --all-features
           --workspace
           --message-format=json | clippy-sarif | tee rust-clippy-results.sarif | sarif-fmt
-      -
-        name: Upload analysis
-        uses: github/codeql-action/upload-sarif@v3
+      - name: Upload analysis
+        uses: github/codeql-action/upload-sarif@v4
         continue-on-error: true
         with:
           sarif_file: rust-clippy-results.sarif
diff --git a/.github/workflows/cargo-publish.yml b/.github/workflows/cargo-publish.yml
index 7592aea4..f956b7fb 100644
--- a/.github/workflows/cargo-publish.yml
+++ b/.github/workflows/cargo-publish.yml
@@ -6,25 +6,26 @@ concurrency:
 
 on:
   repository_dispatch:
-    types: [ deploy, publish, cargo-publish, crates-io ]
+    types: [deploy, publish, cargo-publish, crates-io]
   workflow_dispatch:
     inputs:
       publish:
         default: true
-        description: 'Publish the crate(s) to crates.io?'
+        description: "Publish the crate(s) to crates.io?"
         type: boolean
 
+env:
+  CARGO_TERM_COLOR: always
+  RUST_BACKTRACE: full
+
 jobs:
   crates-io:
+    environment: crates-io
     runs-on: ubuntu-latest
     env:
       CARGO_REGISTRY_TOKEN: ${{ secrets.CARGO_REGISTRY_TOKEN }}
-      CARGO_TERM_COLOR: always
-      RUST_BACKTRACE: full
-    environment:
-      name: crates-io
     outputs:
-      url:  ${{ steps.results.outputs.url }}
+      url: ${{ steps.results.outputs.url }}
     permissions:
       contents: read
       deployments: write
@@ -34,7 +35,9 @@ jobs:
       max-parallel: 1
       matrix:
         package:
+          - concision-traits
           - concision-init
+          - concision-params
           - concision-utils
           - concision-core
           - concision-data
@@ -46,23 +49,23 @@ jobs:
           # non-sdk packages
           - concision-kan
           - concision-s4
+          - concision-snn
           - concision-transformer
           - concision-models
     steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
-      -
-        name: Setup Rust
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+          ref: ${{ github.ref }}
+          token: ${{ secrets.GITHUB_TOKEN }}
+      - name: Setup Rust
         uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
           cache-key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
-      -
-        name: Publish (${{ matrix.package }})
+      - name: Publish (${{ matrix.package }})
         id: publish
         run: cargo publish --locked --package ${{ matrix.package }}
-      -
-        name: Set output(s)
+      - name: Set output(s)
         id: results
-        run:
-          echo "url=https://crates.io/crates/${{ matrix.package }}" >> "$GITHUB_OUTPUT"
+        run: echo "url=https://crates.io/crates/${{ matrix.package }}" >> "$GITHUB_OUTPUT"
diff --git a/.github/workflows/cleanup.yml b/.github/workflows/cleanup.yml
index 338cc169..f442853c 100644
--- a/.github/workflows/cleanup.yml
+++ b/.github/workflows/cleanup.yml
@@ -2,17 +2,16 @@ name: Cleanup
 
 on:
   pull_request:
-    types:
-      - closed
+    types: [closed]
 
 jobs:
-  cache_cleanup:
+  pr_cache_cleanup:
+    name: Cleanup PR Cache(s)
     runs-on: ubuntu-latest
     permissions:
       actions: write
     steps:
-      -
-        name: Cleanup
+      - name: Cleanup
         run: |
           echo "Fetching list of cache keys"
           cacheKeysForPR=$(gh cache list --ref $BRANCH --limit 100 --json id --jq '.[].id')
diff --git a/.github/workflows/nix.yml b/.github/workflows/nix.yml
index 9a7667d8..419b8c3a 100644
--- a/.github/workflows/nix.yml
+++ b/.github/workflows/nix.yml
@@ -6,24 +6,15 @@ concurrency:
 
 on:
   pull_request:
-    branches:
-      - main
-      - $default-branch
-    types:
-      - opened
-      - reopened
-      - synchronize
+    branches: [main, master]
+    types: [edited, opened, ready_for_review, reopened]
   push:
-    branches:
-      - main
-      - $default-branch
-    tags:
-      - v*.*.*
-      - "*-nightly"
+    branches: [main, master]
+    tags: [v*.*.*, "*-nightly"]
   release:
-    types: [ created, edited ]
+    types: [created, edited]
   repository_dispatch:
-    types: [ nix, nix-build ]
+    types: [nix, nix-build]
   workflow_dispatch:
 
 permissions:
@@ -34,17 +25,13 @@ jobs:
     continue-on-error: true
     runs-on: ubuntu-latest
     steps:
-    -
-      uses: actions/checkout@v4
-    -
-      uses: cachix/install-nix-action@v31
-      with:
-        github_access_token: ${{ secrets.GITHUB_TOKEN }}
-    -
-      name: Build
-      id: build
-      run: nix build
-    -
-      name: Check the flake
-      id: check
-      run: nix flake check
+      - uses: actions/checkout@v5
+      - uses: cachix/install-nix-action@v31
+        with:
+          github_access_token: ${{ secrets.GITHUB_TOKEN }}
+      - name: Build
+        id: build
+        run: nix build
+      - name: Check the flake
+        id: check
+        run: nix flake check
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index a6426452..7cb2b6f2 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -2,20 +2,19 @@ name: Release
 
 on:
   release:
-    types:
-      - published
+    types: [published]
   repository_dispatch:
-    types: [ release ]
+    types: [release]
   workflow_dispatch:
     inputs:
       draft:
         default: false
-        description: 'Create a draft release'
+        description: "Create a draft release"
         required: true
         type: boolean
       prerelease:
         default: false
-        description: 'Create a prerelease'
+        description: "Create a prerelease"
         required: true
         type: boolean
 
@@ -23,6 +22,10 @@ permissions:
   contents: write
   discussions: write
 
+env:
+  IS_DRAFT: ${{ github.event.inputs.draft || github.event.release.draft || false }}
+  IS_PRERELEASE: ${{ github.event.inputs.prerelease || github.event.release.prerelease || false }}
+
 jobs:
   publish:
     environment:
@@ -30,33 +33,19 @@ jobs:
       url: https://crates.io/crates/concision
     runs-on: ubuntu-latest
     steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
+      - name: Checkout
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
           ref: ${{ github.ref }}
           repository: ${{ github.repository }}
-      - 
-        name: Publish to crates.io
+      - name: Publish to crates.io
         uses: peter-evans/repository-dispatch@v3
         with:
           event-type: cargo-publish
           client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}"}'
           token: ${{ github.token }}
-  release:
-    continue-on-error: true
-    needs: publish
-    env:
-      IS_PRERELEASE: ${{ github.event.inputs.prerelease || false }}
-      IS_DRAFT: ${{ github.event.inputs.draft || false }}
-    runs-on: ubuntu-latest
-    steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
-      -
-        name: Create release
+      - name: Create release
         uses: softprops/action-gh-release@v2
         with:
           append_body: false
diff --git a/.github/workflows/rust.yml b/.github/workflows/rust.yml
index 2b51fba2..0537e405 100644
--- a/.github/workflows/rust.yml
+++ b/.github/workflows/rust.yml
@@ -10,27 +10,18 @@ env:
 
 on:
   pull_request:
-    branches:
-      - main
-      - $default-branch
-    types:
-      - opened
-      - reopened
-      - synchronize
+    branches: [main, master]
+    types: [edited, opened, ready_for_review, reopened, synchronize]
   push:
-    branches:
-      - main
-      - $default-branch
-    tags:
-      - v*.*.*
-      - "*-nightly"
+    branches: [main, master]
+    tags: [v*.*.*, "*-nightly"]
   repository_dispatch:
-    types: [ rust ]
+    types: [rust]
   workflow_dispatch:
     inputs:
       benchmark:
         default: false
-        description: 'Run benchmarks'
+        description: "Run benchmarks"
         required: true
         type: boolean
 
@@ -40,69 +31,68 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        target: [ x86_64-unknown-linux-gnu ]
+        target: [x86_64-unknown-linux-gnu]
     steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
-      -
-        name: Setup Rust
+      - name: Checkout
+        uses: actions/checkout@v5
+      - name: Setup Rust
         uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
           cache-key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
           target: ${{ matrix.target }}
-      -
-        name: Build the workspace
+      - name: Build the workspace
         run: cargo build --release --locked --workspace --features full --target ${{ matrix.target }}
   benchmark:
     if: ${{ inputs.benchmark || github.event_name == 'push' }}
     runs-on: ubuntu-latest
     outputs:
-      digest: ${{ steps.cargo-bench.outputs.digest }}
-      id: ${{ steps.cargo-bench.outputs.id }}
-      url: ${{ steps.cargo-bench.outputs.url }}
+      digest: ${{ steps.artifacts.outputs.artifact-digest }}
+      id: ${{ steps.artifacts.outputs.artifact-id }}
+      url: ${{ steps.artifacts.outputs.artifact-url }}
     permissions:
       actions: read
       contents: write
+    strategy:
+      fail-fast: false
+      matrix:
+        target: [x86_64-unknown-linux-gnu]
     steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
+      - name: Checkout
+        uses: actions/checkout@v5
+      - name: Setup Rust
+        uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
-          fetch-depth: 0
-          ref: ${{ github.ref }}
-          repository: ${{ github.repository }}
-      -
-        name: Benchmark the workspace
-        id: cargo-bench
-        uses: peter-evans/repository-dispatch@v3
+          cache-key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
+          target: ${{ matrix.target }}
+      - name: Benchmark the workspace
+        run: cargo bench --locked --verbose --workspace --target ${{ matrix.target }} --features full
+      - name: Upload the benchmarks
+        id: artifacts
+        uses: actions/upload-artifact@v5
         with:
-          event-type: cargo-bench
-          client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}"}'
-          token: ${{ github.token }}
+          name: Benchmark Report (${{ github.event.repository.name }})
+          if-no-files-found: error
+          overwrite: true
+          path: target/criterion/
   test:
     needs: build
     runs-on: ubuntu-latest
     strategy:
       fail-fast: false
       matrix:
-        features:  [ full, default ]
-        target: [ x86_64-unknown-linux-gnu ]
+        features: [full, default]
+        target: [x86_64-unknown-linux-gnu]
     steps:
-      -
-        name: Checkout
-        uses: actions/checkout@v4
-      -
-        name: Setup Rust
+      - name: Checkout
+        uses: actions/checkout@v5
+      - name: Setup Rust
         uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
           cache-key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
           target: ${{ matrix.target }}
-      -
-        name: Test (${{ matrix.features }})
+      - name: Test (${{ matrix.features }})
         if: matrix.features != 'default' && matrix.features != 'all'
         run: cargo test -r --locked --workspace --target ${{ matrix.target }} --features ${{ matrix.features }}
-      -
-        name: Test (default)
+      - name: Test (default)
         if: matrix.features == 'default'
         run: cargo test -r --locked --workspace --target ${{ matrix.target }}
diff --git a/Cargo.lock b/Cargo.lock
index 7bc16da6..35a970d5 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -2,36 +2,15 @@
 # It is not intended for manual editing.
 version = 4
 
-[[package]]
-name = "addr2line"
-version = "0.24.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "dfbe277e56a376000877090da837660b4427aad530e3028d44e0bffe4f89a1c1"
-dependencies = [
- "gimli",
-]
-
-[[package]]
-name = "adler2"
-version = "2.0.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "320119579fcad9c21884f5c4861d16174d0e06250625266f50fe6898340abefa"
-
 [[package]]
 name = "aho-corasick"
-version = "1.1.3"
+version = "1.1.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8e60d3430d3a69478ad0993f19238d2df97c507009a52b3c10addcd7f6bcb916"
+checksum = "ddd31a130427c27518df266943a5308ed92d4b226cc639f5a8f1002816174301"
 dependencies = [
  "memchr",
 ]
 
-[[package]]
-name = "android-tzdata"
-version = "0.1.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e999941b234f3131b00bc13c22d06e8c5ff726d1b6318ac7eb276997bbb4fef0"
-
 [[package]]
 name = "android_system_properties"
 version = "0.1.5"
@@ -49,15 +28,15 @@ checksum = "4b46cbb362ab8752921c97e041f5e366ee6297bd428a31275b9fcf1e380f7299"
 
 [[package]]
 name = "anstyle"
-version = "1.0.11"
+version = "1.0.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "862ed96ca487e809f1c8e5a8447f6ee2cf102f846893800b20cebdf541fc6bbd"
+checksum = "5192cca8006f1fd4f7237516f40fa183bb07f8fbdfedaa0036de5ea9b0b45e78"
 
 [[package]]
 name = "anyhow"
-version = "1.0.98"
+version = "1.0.100"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e16d2d3311acee920a9eb8d33b8cbc1787ce4a264e85f964c2404b969bdcd487"
+checksum = "a23eb6b1614318a8071c9b2521f36b424b2c83db5eb3a0fead4a6c0809af6e61"
 
 [[package]]
 name = "approx"
@@ -69,16 +48,10 @@ dependencies = [
 ]
 
 [[package]]
-name = "arrayref"
-version = "0.3.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "76a2e8124351fda1ef8aaaa3bbd7ebbcb486bbcd4225aca0aa0d84bb2db8fecb"
-
-[[package]]
-name = "arrayvec"
-version = "0.7.6"
+name = "atomic-waker"
+version = "1.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7c02d123df017efcdfbd739ef81735b36c5ba83ec3c59c80a9d7ecc718f92e50"
+checksum = "1505bd5d3d116872e7271a6d4e16d81d0c8570876c8de68093a09ac269d8aac0"
 
 [[package]]
 name = "autocfg"
@@ -86,65 +59,17 @@ version = "1.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "c08606f8c3cbf4ce6ec8e28fb0014a2c086708fe954eaa885384a6165172e7e8"
 
-[[package]]
-name = "backtrace"
-version = "0.3.75"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6806a6321ec58106fea15becdad98371e28d92ccbc7c8f1b3b6dd724fe8f1002"
-dependencies = [
- "addr2line",
- "cfg-if",
- "libc",
- "miniz_oxide",
- "object",
- "rustc-demangle",
- "windows-targets",
-]
-
 [[package]]
 name = "base64"
 version = "0.22.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "72b3254f16251a8381aa12e40e3c4d2f0199f8c6508fbecb9d91f575e0fbb8c6"
 
-[[package]]
-name = "bincode"
-version = "2.0.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "36eaf5d7b090263e8150820482d5d93cd964a81e4019913c972f4edcc6edb740"
-dependencies = [
- "bincode_derive",
- "serde",
- "unty",
-]
-
-[[package]]
-name = "bincode_derive"
-version = "2.0.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bf95709a440f45e986983918d0e8a1f30a9b1df04918fc828670606804ac3c09"
-dependencies = [
- "virtue",
-]
-
 [[package]]
 name = "bitflags"
-version = "2.9.1"
+version = "2.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1b8e56985ec62d17e9c1001dc89c88ecd7dc08e47eba5ec7c29c7b5eeecde967"
-
-[[package]]
-name = "blake3"
-version = "1.8.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3888aaa89e4b2a40fca9848e400f6a658a5a3978de7be858e209cafa8be9a4a0"
-dependencies = [
- "arrayref",
- "arrayvec",
- "cc",
- "cfg-if",
- "constant_time_eq",
-]
+checksum = "812e12b5285cc515a9c72a5c1d3b6d46a19dac5acfef5265968c166106e31dd3"
 
 [[package]]
 name = "bumpalo"
@@ -154,9 +79,9 @@ checksum = "46c5e41b57b8bba42a04676d81cb89e9ee8e859a1a66f80a5a72e1cb76b34d43"
 
 [[package]]
 name = "bytes"
-version = "1.10.1"
+version = "1.11.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d71b6127be86fdcfddb610f7182ac57211d4b18a3e9c82eb2d17662f2227ad6a"
+checksum = "b35204fbdc0b3f4446b89fc1ac2cf84a8a68971995d0bf2e925ec7cd960f9cb3"
 
 [[package]]
 name = "cast"
@@ -175,31 +100,29 @@ dependencies = [
 
 [[package]]
 name = "cc"
-version = "1.2.27"
+version = "1.2.47"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d487aa071b5f64da6f19a3e848e3578944b726ee5a4854b82172f02aa876bfdc"
+checksum = "cd405d82c84ff7f35739f175f67d8b9fb7687a0e84ccdc78bd3568839827cf07"
 dependencies = [
+ "find-msvc-tools",
  "shlex",
 ]
 
 [[package]]
 name = "cfg-if"
-version = "1.0.1"
+version = "1.0.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9555578bc9e57714c812a1f84e4fc5b4d21fcb063490c624de019f7464c91268"
+checksum = "9330f8b2ff13f34540b44e946ef35111825727b38d33286ef986142615121801"
 
 [[package]]
 name = "chrono"
-version = "0.4.41"
+version = "0.4.42"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c469d952047f47f91b68d1cba3f10d63c11d73e4636f24f08daf0278abf01c4d"
+checksum = "145052bdd345b87320e369255277e3fb5152762ad123a901ef5c262dd38fe8d2"
 dependencies = [
- "android-tzdata",
  "iana-time-zone",
- "js-sys",
  "num-traits",
  "serde",
- "wasm-bindgen",
  "windows-link",
 ]
 
@@ -232,18 +155,18 @@ dependencies = [
 
 [[package]]
 name = "clap"
-version = "4.5.40"
+version = "4.5.53"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "40b6887a1d8685cebccf115538db5c0efe625ccac9696ad45c409d96566e910f"
+checksum = "c9e340e012a1bf4935f5282ed1436d1489548e8f72308207ea5df0e23d2d03f8"
 dependencies = [
  "clap_builder",
 ]
 
 [[package]]
 name = "clap_builder"
-version = "4.5.40"
+version = "4.5.53"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e0c66c08ce9f0c698cbce5c0279d0bb6ac936d8674174fe48f736533b964f59e"
+checksum = "d76b5d13eaa18c901fd2f7fca939fefe3a0727a953561fefdf3b2922b8569d00"
 dependencies = [
  "anstyle",
  "clap_lex",
@@ -251,13 +174,13 @@ dependencies = [
 
 [[package]]
 name = "clap_lex"
-version = "0.7.5"
+version = "0.7.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b94f61472cee1439c0b966b47e3aca9ae07e45d070759512cd390ea2bebc6675"
+checksum = "a1d728cc89cf3aee9ff92b05e62b19ee65a02b5702cff7d5a377e32c6ae29d8d"
 
 [[package]]
 name = "concision"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
@@ -277,26 +200,24 @@ dependencies = [
 
 [[package]]
 name = "concision-core"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
- "anyhow",
  "approx",
  "concision-init",
+ "concision-params",
+ "concision-traits",
  "concision-utils",
  "getrandom",
  "lazy_static",
  "ndarray",
- "ndtensor",
  "num",
  "num-complex",
  "num-traits",
  "paste",
- "rand 0.9.1",
+ "rand 0.9.2",
  "rand_distr",
  "rayon",
  "rustfft",
- "scsys",
- "scsys-derive",
  "serde",
  "serde_derive",
  "serde_json",
@@ -304,13 +225,13 @@ dependencies = [
  "strum",
  "thiserror",
  "tracing",
+ "variants",
 ]
 
 [[package]]
 name = "concision-data"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
- "anyhow",
  "approx",
  "concision-core",
  "ndarray",
@@ -319,16 +240,16 @@ dependencies = [
  "num-traits",
  "rayon",
  "reqwest",
- "scsys",
  "serde",
  "serde_json",
  "thiserror",
  "tracing",
+ "variants",
 ]
 
 [[package]]
 name = "concision-derive"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -337,7 +258,7 @@ dependencies = [
 
 [[package]]
 name = "concision-ext"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
@@ -349,19 +270,18 @@ dependencies = [
  "num-traits",
  "rayon",
  "rustfft",
- "scsys",
  "serde",
  "serde_derive",
  "serde_json",
  "tracing",
  "tracing-subscriber",
+ "variants",
 ]
 
 [[package]]
 name = "concision-init"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
- "anyhow",
  "approx",
  "getrandom",
  "lazy_static",
@@ -370,7 +290,7 @@ dependencies = [
  "num-complex",
  "num-traits",
  "paste",
- "rand 0.9.1",
+ "rand 0.9.2",
  "rand_distr",
  "serde",
  "serde_derive",
@@ -383,7 +303,7 @@ dependencies = [
 
 [[package]]
 name = "concision-kan"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
@@ -395,7 +315,7 @@ dependencies = [
 
 [[package]]
 name = "concision-macros"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -404,7 +324,7 @@ dependencies = [
 
 [[package]]
 name = "concision-models"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
@@ -416,19 +336,20 @@ dependencies = [
  "lazy_static",
  "ndarray",
  "num-traits",
- "scsys",
  "tracing",
  "tracing-subscriber",
+ "variants",
 ]
 
 [[package]]
 name = "concision-neural"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
  "concision-core",
  "concision-data",
+ "concision-params",
  "either",
  "getrandom",
  "lazy_static",
@@ -437,12 +358,10 @@ dependencies = [
  "num-complex",
  "num-traits",
  "paste",
- "rand 0.9.1",
+ "rand 0.9.2",
  "rand_distr",
  "rayon",
  "rustfft",
- "scsys",
- "scsys-derive",
  "serde",
  "serde_derive",
  "serde_json",
@@ -450,23 +369,78 @@ dependencies = [
  "strum",
  "thiserror",
  "tracing",
+ "variants",
+]
+
+[[package]]
+name = "concision-params"
+version = "0.2.8"
+dependencies = [
+ "approx",
+ "concision-init",
+ "concision-traits",
+ "getrandom",
+ "lazy_static",
+ "ndarray",
+ "num-complex",
+ "num-traits",
+ "rand 0.9.2",
+ "rand_distr",
+ "rayon",
+ "serde",
+ "serde_derive",
+ "serde_json",
+ "thiserror",
+ "variants",
 ]
 
 [[package]]
 name = "concision-s4"
-version = "0.2.7"
+version = "0.2.8"
+dependencies = [
+ "anyhow",
+ "approx",
+ "concision",
+ "ndarray",
+ "num-traits",
+ "tracing",
+]
+
+[[package]]
+name = "concision-snn"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
  "concision",
  "ndarray",
  "num-traits",
+ "serde",
+ "serde_derive",
+ "serde_json",
  "tracing",
 ]
 
+[[package]]
+name = "concision-traits"
+version = "0.2.8"
+dependencies = [
+ "approx",
+ "getrandom",
+ "lazy_static",
+ "ndarray",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "rand 0.9.2",
+ "rand_distr",
+ "thiserror",
+ "variants",
+]
+
 [[package]]
 name = "concision-transformer"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
@@ -478,7 +452,7 @@ dependencies = [
 
 [[package]]
 name = "concision-utils"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
  "anyhow",
  "approx",
@@ -489,12 +463,10 @@ dependencies = [
  "num-complex",
  "num-traits",
  "paste",
- "rand 0.9.1",
+ "rand 0.9.2",
  "rand_distr",
  "rayon",
  "rustfft",
- "scsys",
- "scsys-derive",
  "serde",
  "serde_derive",
  "serde_json",
@@ -502,26 +474,9 @@ dependencies = [
  "strum",
  "thiserror",
  "tracing",
+ "variants",
 ]
 
-[[package]]
-name = "config"
-version = "0.15.11"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "595aae20e65c3be792d05818e8c63025294ac3cb7e200f11459063a352a6ef80"
-dependencies = [
- "pathdiff",
- "serde",
- "serde_json",
- "winnow",
-]
-
-[[package]]
-name = "constant_time_eq"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7c74b8349d32d297c9134b8c88677813a227df8f779daa29bfc29c183fe3dca6"
-
 [[package]]
 name = "core-foundation-sys"
 version = "0.8.7"
@@ -530,16 +485,16 @@ checksum = "773648b94d0e5d620f64f280777445740e61fe701025087ec8b57f45c791888b"
 
 [[package]]
 name = "criterion"
-version = "0.6.0"
+version = "0.7.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3bf7af66b0989381bd0be551bd7cc91912a655a58c6918420c9527b1fd8b4679"
+checksum = "e1c047a62b0cc3e145fa84415a3191f628e980b194c2755aa12300a4e6cbd928"
 dependencies = [
  "anes",
  "cast",
  "ciborium",
  "clap",
  "criterion-plot",
- "itertools 0.13.0",
+ "itertools",
  "num-traits",
  "oorandom",
  "plotters",
@@ -553,12 +508,12 @@ dependencies = [
 
 [[package]]
 name = "criterion-plot"
-version = "0.5.0"
+version = "0.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6b50826342786a51a89e2da3a28f1c32b06e387201bc2d19791f622c673706b1"
+checksum = "9b1bcc0dc7dfae599d84ad0b1a55f80cde8af3725da8313b528da95ef783e338"
 dependencies = [
  "cast",
- "itertools 0.10.5",
+ "itertools",
 ]
 
 [[package]]
@@ -592,16 +547,6 @@ version = "0.2.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "460fbee9c2c2f33933d720630a6a0bac33ba7053db5344fac858d4b8952d77d5"
 
-[[package]]
-name = "crypto-common"
-version = "0.1.6"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1bfb12502f3fc46cca1bb51ac28df9d618d813cdc3d2f25b9fe775a34af26bb3"
-dependencies = [
- "generic-array 0.14.7",
- "typenum",
-]
-
 [[package]]
 name = "darling"
 version = "0.20.11"
@@ -639,21 +584,12 @@ dependencies = [
 
 [[package]]
 name = "deranged"
-version = "0.4.0"
+version = "0.5.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9c9e6a11ca8224451684bc0d7d5a7adbf8f2fd6887261a1cfc3c0432f9d4068e"
+checksum = "ececcb659e7ba858fb4f10388c250a7252eb0a27373f1a72b8748afdd248e587"
 dependencies = [
  "powerfmt",
- "serde",
-]
-
-[[package]]
-name = "digest"
-version = "0.10.7"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ed9a281f7bc9b7576e61468ba615a66a5c8cfdff42420a70aa82701a3b1e292"
-dependencies = [
- "crypto-common",
+ "serde_core",
 ]
 
 [[package]]
@@ -679,6 +615,12 @@ version = "1.0.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "877a4ace8713b0bcf2a4e7eec82529c029f1d0619886d18145fea96c3ffe5c0f"
 
+[[package]]
+name = "find-msvc-tools"
+version = "0.1.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3a3076410a55c90011c298b04d0cfa770b00fa04e1e3c97d3f6c9de105a03844"
+
 [[package]]
 name = "fnv"
 version = "1.0.7"
@@ -687,9 +629,9 @@ checksum = "3f9eec918d3f24069decb9af1554cad7c880e2da24a9afd88aca000531ab82c1"
 
 [[package]]
 name = "form_urlencoded"
-version = "1.2.1"
+version = "1.2.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e13624c2627564efccf4934284bdd98cbaa14e79b0b5a141218e507b3a823456"
+checksum = "cb4cb245038516f5f85277875cdaa4f7d2c9a0fa0468de06ed190163b1581fcf"
 dependencies = [
  "percent-encoding",
 ]
@@ -727,54 +669,29 @@ dependencies = [
  "pin-utils",
 ]
 
-[[package]]
-name = "generic-array"
-version = "0.14.7"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "85649ca51fd72272d7821adaf274ad91c288277713d9c18820d8499a7ff69e9a"
-dependencies = [
- "typenum",
- "version_check",
-]
-
-[[package]]
-name = "generic-array"
-version = "1.2.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e8c8444bc9d71b935156cc0ccab7f622180808af7867b1daae6547d773591703"
-dependencies = [
- "serde",
- "typenum",
-]
-
 [[package]]
 name = "getrandom"
-version = "0.3.3"
+version = "0.3.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "26145e563e54f2cadc477553f1ec5ee650b00862f0a58bcd12cbdc5f0ea2d2f4"
+checksum = "899def5c37c4fd7b2664648c28120ecec138e4d395b459e5ca34f9cce2dd77fd"
 dependencies = [
  "cfg-if",
  "js-sys",
  "libc",
  "r-efi",
- "wasi 0.14.2+wasi-0.2.4",
+ "wasip2",
  "wasm-bindgen",
 ]
 
-[[package]]
-name = "gimli"
-version = "0.31.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "07e28edb80900c19c28f1072f2e8aeca7fa06b23cd4169cefe1af5aa3260783f"
-
 [[package]]
 name = "half"
-version = "2.6.0"
+version = "2.7.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "459196ed295495a68f7d7fe1d84f6c4b7ff0e21fe3017b2f283c6fac3ad803c9"
+checksum = "6ea2d84b969582b4b1864a92dc5d27cd2b77b622a8d79306834f1be5ba20d84b"
 dependencies = [
  "cfg-if",
  "crunchy",
+ "zerocopy",
 ]
 
 [[package]]
@@ -785,9 +702,9 @@ checksum = "8a9ee70c43aaf417c914396645a0fa852624801b24ebb7ae78fe8272889ac888"
 
 [[package]]
 name = "hashbrown"
-version = "0.15.4"
+version = "0.16.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5971ac85611da7067dbfcabef3c70ebb5606018acd9e2a3903a0da507521e0d5"
+checksum = "841d1cc9bed7f9236f321df977030373f4a4163ae1a7dbfe1a51a2c1a51d9100"
 
 [[package]]
 name = "heck"
@@ -803,12 +720,11 @@ checksum = "7f24254aa9a54b5c858eaee2f5bccdb46aaf0e486a595ed5fd8f86ba55232a70"
 
 [[package]]
 name = "http"
-version = "1.3.1"
+version = "1.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f4a85d31aea989eead29a3aaf9e1115a180df8282431156e533de47660892565"
+checksum = "e3ba2a386d7f85a81f119ad7498ebe444d2e22c2af0b86b069416ace48b3311a"
 dependencies = [
  "bytes",
- "fnv",
  "itoa",
 ]
 
@@ -843,18 +759,20 @@ checksum = "6dbf3de79e51f3d586ab4cb9d5c3e2c14aa28ed23d180cf89b4df0454a69cc87"
 
 [[package]]
 name = "hyper"
-version = "1.6.0"
+version = "1.8.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cc2b571658e38e0c01b1fdca3bbbe93c00d3d71693ff2770043f8c29bc7d6f80"
+checksum = "2ab2d4f250c3d7b1c9fcdff1cece94ea4e2dfbec68614f7b87cb205f24ca9d11"
 dependencies = [
+ "atomic-waker",
  "bytes",
  "futures-channel",
- "futures-util",
+ "futures-core",
  "http",
  "http-body",
  "httparse",
  "itoa",
  "pin-project-lite",
+ "pin-utils",
  "smallvec",
  "tokio",
  "want",
@@ -862,9 +780,9 @@ dependencies = [
 
 [[package]]
 name = "hyper-util"
-version = "0.1.14"
+version = "0.1.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "dc2fdfdbff08affe55bb779f33b053aa1fe5dd5b54c257343c17edfa55711bdb"
+checksum = "52e9a2a24dc5c6821e71a7030e1e14b7b632acac55c40e9d2e082c621261bb56"
 dependencies = [
  "base64",
  "bytes",
@@ -886,9 +804,9 @@ dependencies = [
 
 [[package]]
 name = "iana-time-zone"
-version = "0.1.63"
+version = "0.1.64"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b0c919e5debc312ad217002b8048a17b7d83f80703865bbfcfebb0458b0b27d8"
+checksum = "33e57f83510bb73707521ebaffa789ec8caf86f9657cad665b092b581d40e9fb"
 dependencies = [
  "android_system_properties",
  "core-foundation-sys",
@@ -910,9 +828,9 @@ dependencies = [
 
 [[package]]
 name = "icu_collections"
-version = "2.0.0"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "200072f5d0e3614556f94a9930d5dc3e0662a652823904c3a75dc3b0af7fee47"
+checksum = "4c6b649701667bbe825c3b7e6388cb521c23d88644678e83c0c4d0a621a34b43"
 dependencies = [
  "displaydoc",
  "potential_utf",
@@ -923,9 +841,9 @@ dependencies = [
 
 [[package]]
 name = "icu_locale_core"
-version = "2.0.0"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0cde2700ccaed3872079a65fb1a78f6c0a36c91570f28755dda67bc8f7d9f00a"
+checksum = "edba7861004dd3714265b4db54a3c390e880ab658fec5f7db895fae2046b5bb6"
 dependencies = [
  "displaydoc",
  "litemap",
@@ -936,11 +854,10 @@ dependencies = [
 
 [[package]]
 name = "icu_normalizer"
-version = "2.0.0"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "436880e8e18df4d7bbc06d58432329d6458cc84531f7ac5f024e93deadb37979"
+checksum = "5f6c8828b67bf8908d82127b2054ea1b4427ff0230ee9141c54251934ab1b599"
 dependencies = [
- "displaydoc",
  "icu_collections",
  "icu_normalizer_data",
  "icu_properties",
@@ -951,42 +868,38 @@ dependencies = [
 
 [[package]]
 name = "icu_normalizer_data"
-version = "2.0.0"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "00210d6893afc98edb752b664b8890f0ef174c8adbb8d0be9710fa66fbbf72d3"
+checksum = "7aedcccd01fc5fe81e6b489c15b247b8b0690feb23304303a9e560f37efc560a"
 
 [[package]]
 name = "icu_properties"
-version = "2.0.1"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "016c619c1eeb94efb86809b015c58f479963de65bdb6253345c1a1276f22e32b"
+checksum = "e93fcd3157766c0c8da2f8cff6ce651a31f0810eaa1c51ec363ef790bbb5fb99"
 dependencies = [
- "displaydoc",
  "icu_collections",
  "icu_locale_core",
  "icu_properties_data",
  "icu_provider",
- "potential_utf",
  "zerotrie",
  "zerovec",
 ]
 
 [[package]]
 name = "icu_properties_data"
-version = "2.0.1"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "298459143998310acd25ffe6810ed544932242d3f07083eee1084d83a71bd632"
+checksum = "02845b3647bb045f1100ecd6480ff52f34c35f82d9880e029d329c21d1054899"
 
 [[package]]
 name = "icu_provider"
-version = "2.0.0"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "03c80da27b5f4187909049ee2d72f276f0d9f99a42c306bd0131ecfe04d8e5af"
+checksum = "85962cf0ce02e1e0a629cc34e7ca3e373ce20dda4c4d7294bbd0bf1fdb59e614"
 dependencies = [
  "displaydoc",
  "icu_locale_core",
- "stable_deref_trait",
- "tinystr",
  "writeable",
  "yoke",
  "zerofrom",
@@ -1002,9 +915,9 @@ checksum = "b9e0384b61958566e926dc50660321d12159025e767c18e043daf26b70104c39"
 
 [[package]]
 name = "idna"
-version = "1.0.3"
+version = "1.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "686f825264d630750a544639377bae737628043f20d38bbc029e8f29ea968a7e"
+checksum = "3b0875f23caa03898994f6ddc501886a45c7d3d62d04d2d90788d47be1b1e4de"
 dependencies = [
  "idna_adapter",
  "smallvec",
@@ -1034,24 +947,14 @@ dependencies = [
 
 [[package]]
 name = "indexmap"
-version = "2.10.0"
+version = "2.12.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fe4cd85333e22411419a0bcae1297d25e58c9443848b11dc6a86fefe8c78a661"
+checksum = "0ad4bb2b565bca0645f4d68c5c9af97fba094e9791da685bf83cb5f3ce74acf2"
 dependencies = [
  "equivalent",
- "hashbrown 0.15.4",
+ "hashbrown 0.16.1",
  "serde",
-]
-
-[[package]]
-name = "io-uring"
-version = "0.7.8"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b86e202f00093dcba4275d4636b93ef9dd75d025ae560d2521b45ea28ab49013"
-dependencies = [
- "bitflags",
- "cfg-if",
- "libc",
+ "serde_core",
 ]
 
 [[package]]
@@ -1062,23 +965,14 @@ checksum = "469fb0b9cefa57e3ef31275ee7cacb78f2fdca44e4765491884a2b119d4eb130"
 
 [[package]]
 name = "iri-string"
-version = "0.7.8"
+version = "0.7.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "dbc5ebe9c3a1a7a5127f920a418f7585e9e758e911d0466ed004f393b0e380b2"
+checksum = "4f867b9d1d896b67beb18518eda36fdb77a32ea590de864f1325b294a6d14397"
 dependencies = [
  "memchr",
  "serde",
 ]
 
-[[package]]
-name = "itertools"
-version = "0.10.5"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b0fd2260e829bddf4cb6ea802289de2f86d6a7a690192fbe91b3f46e0f2c8473"
-dependencies = [
- "either",
-]
-
 [[package]]
 name = "itertools"
 version = "0.13.0"
@@ -1096,9 +990,9 @@ checksum = "4a5f13b858c8d314ee3e8f639011f7ccefe71f97f96e50151fb991f267928e2c"
 
 [[package]]
 name = "js-sys"
-version = "0.3.77"
+version = "0.3.82"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1cfaf33c695fc6e08064efbc1f72ec937429614f25eef83af942d0e227c3a28f"
+checksum = "b011eec8cc36da2aab2d5cff675ec18454fad408585853910a202391cf9f8e65"
 dependencies = [
  "once_cell",
  "wasm-bindgen",
@@ -1112,9 +1006,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
 
 [[package]]
 name = "libc"
-version = "0.2.174"
+version = "0.2.177"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1171693293099992e19cddea4e8b849964e9846f4acee11b3948bcc337be8776"
+checksum = "2874a2af47a2325c2001a6e6fad9b16a53b802102b528163885171cf92b15976"
 
 [[package]]
 name = "libm"
@@ -1124,23 +1018,23 @@ checksum = "f9fbbcab51052fe104eb5e5d351cf728d30a5be1fe14d9be8a3b097481fb97de"
 
 [[package]]
 name = "litemap"
-version = "0.8.0"
+version = "0.8.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "241eaef5fd12c88705a01fc1066c48c4b36e0dd4377dcdc7ec3942cea7a69956"
+checksum = "6373607a59f0be73a39b6fe456b8192fcc3585f602af20751600e974dd455e77"
 
 [[package]]
 name = "log"
-version = "0.4.27"
+version = "0.4.28"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "13dc2df351e3202783a1fe0d44375f7295ffb4049267b0f3018346dc122a1d94"
+checksum = "34080505efa8e45a4b816c349525ebe327ceaa8559756f0356cba97ef3bf7432"
 
 [[package]]
 name = "matchers"
-version = "0.1.0"
+version = "0.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8263075bb86c5a1b1427b5ae862e8889656f126e9f77c484496e8b47cf5c5558"
+checksum = "d1525a2a28c7f4fa0fc98bb91ae755d1e2d1505079e05539e35bc876b5d65ae9"
 dependencies = [
- "regex-automata 0.1.10",
+ "regex-automata",
 ]
 
 [[package]]
@@ -1155,35 +1049,26 @@ dependencies = [
 
 [[package]]
 name = "memchr"
-version = "2.7.5"
+version = "2.7.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "32a282da65faaf38286cf3be983213fcf1d2e2a58700e808f83f4ea9a4804bc0"
-
-[[package]]
-name = "miniz_oxide"
-version = "0.8.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1fa76a2c86f704bdb222d66965fb3d63269ce38518b83cb0575fca855ebb6316"
-dependencies = [
- "adler2",
-]
+checksum = "f52b00d39961fc5b2736ea853c9cc86238e165017a493d1d5c8eac6bdc4cc273"
 
 [[package]]
 name = "mio"
-version = "1.0.4"
+version = "1.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "78bed444cc8a2160f01cbcf811ef18cac863ad68ae8ca62092e8db51d51c761c"
+checksum = "69d83b0086dc8ecf3ce9ae2874b2d1290252e2a30720bea58a5c6639b0092873"
 dependencies = [
  "libc",
- "wasi 0.11.1+wasi-snapshot-preview1",
- "windows-sys 0.59.0",
+ "wasi",
+ "windows-sys 0.61.2",
 ]
 
 [[package]]
 name = "ndarray"
-version = "0.16.1"
+version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "882ed72dce9365842bf196bdeedf5055305f11fc8c03dee7bb0194a6cad34841"
+checksum = "0c7c9125e8f6f10c9da3aad044cc918cf8784fa34de857b1aa68038eb05a50a9"
 dependencies = [
  "approx",
  "cblas-sys",
@@ -1199,42 +1084,13 @@ dependencies = [
  "serde",
 ]
 
-[[package]]
-name = "ndtensor"
-version = "0.1.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ea8ab4dd20883ddf58cdbade1810f8840d0d420f33e5143b407ec7c3102ae2ec"
-dependencies = [
- "anyhow",
- "approx",
- "getrandom",
- "ndarray",
- "num",
- "num-complex",
- "num-traits",
- "paste",
- "rand 0.9.1",
- "rand_distr",
- "rayon",
- "scsys",
- "scsys-derive",
- "serde",
- "serde_derive",
- "serde_json",
- "smart-default",
- "strum",
- "thiserror",
- "tracing",
-]
-
 [[package]]
 name = "nu-ansi-term"
-version = "0.46.0"
+version = "0.50.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "77a8165726e8236064dbb45459242600304b42a5ea24ee2948e18e023bf7ba84"
+checksum = "7957b9740744892f114936ab4a57b3f487491bbeafaf8083688b16841a4240e5"
 dependencies = [
- "overload",
- "winapi",
+ "windows-sys 0.61.2",
 ]
 
 [[package]]
@@ -1322,15 +1178,6 @@ dependencies = [
  "libm",
 ]
 
-[[package]]
-name = "object"
-version = "0.36.7"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "62948e14d923ea95ea2c7c86c71013138b66525b86bdc08d2dcc262bdb497b87"
-dependencies = [
- "memchr",
-]
-
 [[package]]
 name = "once_cell"
 version = "1.21.3"
@@ -1343,29 +1190,17 @@ version = "11.1.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d6790f58c7ff633d8771f42965289203411a5e5c68388703c06e14f24770b41e"
 
-[[package]]
-name = "overload"
-version = "0.1.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b15813163c1d831bf4a13c3610c05c0d03b39feb07f7e09fa234dac9b15aaf39"
-
 [[package]]
 name = "paste"
 version = "1.0.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "57c0d7b74b563b49d38dae00a0c37d4d6de9b432382b2892f0574ddcae73fd0a"
 
-[[package]]
-name = "pathdiff"
-version = "0.2.3"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "df94ce210e5bc13cb6651479fa48d14f601d9858cfe0467f43ae157023b938d3"
-
 [[package]]
 name = "percent-encoding"
-version = "2.3.1"
+version = "2.3.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e3148f5046208a5d56bcfc03053e3ca6334e51da8dfb19b6cdc8b306fae3283e"
+checksum = "9b4f627cb1b25917193a259e49bdad08f671f8d9708acfd5fe0a8c1455d87220"
 
 [[package]]
 name = "pin-project-lite"
@@ -1424,9 +1259,9 @@ dependencies = [
 
 [[package]]
 name = "potential_utf"
-version = "0.1.2"
+version = "0.1.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e5a7c30837279ca13e7c867e9e40053bc68740f988cb07f7ca6df43cc734b585"
+checksum = "b73949432f5e2a09657003c25bca5e19a0e9c84f8058ca374f49e0ebe605af77"
 dependencies = [
  "zerovec",
 ]
@@ -1457,18 +1292,18 @@ dependencies = [
 
 [[package]]
 name = "proc-macro2"
-version = "1.0.95"
+version = "1.0.103"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "02b3e5e68a3a1a02aad3ec490a98007cbc13c37cbe84a3cd7b8e406d76e7f778"
+checksum = "5ee95bc4ef87b8d5ba32e8b7714ccc834865276eab0aed5c9958d00ec45f49e8"
 dependencies = [
  "unicode-ident",
 ]
 
 [[package]]
 name = "quote"
-version = "1.0.40"
+version = "1.0.42"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1885c039570dc00dcb4ff087a89e185fd56bae234ddc7f056a945bf36467248d"
+checksum = "a338cc41d27e6cc6dce6cefc13a0729dfbb81c262b1f519331575dd80ef3067f"
 dependencies = [
  "proc-macro2",
 ]
@@ -1490,9 +1325,9 @@ dependencies = [
 
 [[package]]
 name = "rand"
-version = "0.9.1"
+version = "0.9.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9fbfd9d094a40bf3ae768db9361049ace4c0e04a4fd6b359518bd7b73a73dd97"
+checksum = "6db2770f06117d490610c7488547d543617b21bfa07796d7a12f6f1bd53850d1"
 dependencies = [
  "rand_chacha",
  "rand_core 0.9.3",
@@ -1532,7 +1367,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "6a8615d50dcf34fa31f7ab52692afec947c4dd0ab803cc87cb3b0b4570ff7463"
 dependencies = [
  "num-traits",
- "rand 0.9.1",
+ "rand 0.9.2",
  "serde",
  "serde_with",
 ]
@@ -1545,9 +1380,9 @@ checksum = "60a357793950651c4ed0f3f52338f53b2f809f32d83a07f72909fa13e4c6c1e3"
 
 [[package]]
 name = "rayon"
-version = "1.10.0"
+version = "1.11.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b418a60154510ca1a002a752ca9714984e21e4241e804d32555251faf8b78ffa"
+checksum = "368f01d005bf8fd9b1206fb6fa653e6c4a81ceb1466406b81792d87c5677a58f"
 dependencies = [
  "either",
  "rayon-core",
@@ -1556,9 +1391,9 @@ dependencies = [
 
 [[package]]
 name = "rayon-core"
-version = "1.12.1"
+version = "1.13.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1465873a3dfdaa8ae7cb14b4383657caab0b3e8a0aa9ae8e04b044854c8dfce2"
+checksum = "22e18b0f0062d30d4230b2e85ff77fdfe4326feb054b9783a3460d8435c8ab91"
 dependencies = [
  "crossbeam-deque",
  "crossbeam-utils",
@@ -1567,53 +1402,38 @@ dependencies = [
 
 [[package]]
 name = "regex"
-version = "1.11.1"
+version = "1.12.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b544ef1b4eac5dc2db33ea63606ae9ffcfac26c1416a2806ae0bf5f56b201191"
+checksum = "843bc0191f75f3e22651ae5f1e72939ab2f72a4bc30fa80a066bd66edefc24d4"
 dependencies = [
  "aho-corasick",
  "memchr",
- "regex-automata 0.4.9",
- "regex-syntax 0.8.5",
+ "regex-automata",
+ "regex-syntax",
 ]
 
 [[package]]
 name = "regex-automata"
-version = "0.1.10"
+version = "0.4.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6c230d73fb8d8c1b9c0b3135c5142a8acee3a0558fb8db5cf1cb65f8d7862132"
-dependencies = [
- "regex-syntax 0.6.29",
-]
-
-[[package]]
-name = "regex-automata"
-version = "0.4.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "809e8dc61f6de73b46c85f4c96486310fe304c434cfa43669d7b40f711150908"
+checksum = "5276caf25ac86c8d810222b3dbb938e512c55c6831a10f3e6ed1c93b84041f1c"
 dependencies = [
  "aho-corasick",
  "memchr",
- "regex-syntax 0.8.5",
+ "regex-syntax",
 ]
 
 [[package]]
 name = "regex-syntax"
-version = "0.6.29"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f162c6dd7b008981e4d40210aca20b4bd0f9b60ca9271061b07f78537722f2e1"
-
-[[package]]
-name = "regex-syntax"
-version = "0.8.5"
+version = "0.8.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2b15c43186be67a4fd63bee50d0303afffcef381492ebe2c5d87f324e1b8815c"
+checksum = "7a2d987857b319362043e95f5353c0535c1f58eec5336fdfcf626430af7def58"
 
 [[package]]
 name = "reqwest"
-version = "0.12.22"
+version = "0.12.24"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cbc931937e6ca3a06e3b6c0aa7841849b160a90351d6ab467a8b9b9959767531"
+checksum = "9d0946410b9f7b082a427e4ef5c8ff541a88b357bc6c637c40db3a68ac70a36f"
 dependencies = [
  "base64",
  "bytes",
@@ -1641,17 +1461,11 @@ dependencies = [
  "web-sys",
 ]
 
-[[package]]
-name = "rustc-demangle"
-version = "0.1.25"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "989e6739f80c4ad5b13e0fd7fe89531180375b18520cc8c82080e4dc4035b84f"
-
 [[package]]
 name = "rustfft"
-version = "6.4.0"
+version = "6.4.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c6f140db74548f7c9d7cce60912c9ac414e74df5e718dc947d514b051b42f3f4"
+checksum = "21db5f9893e91f41798c88680037dba611ca6674703c1a18601b01a72c8adb89"
 dependencies = [
  "num-complex",
  "num-integer",
@@ -1663,9 +1477,9 @@ dependencies = [
 
 [[package]]
 name = "rustversion"
-version = "1.0.21"
+version = "1.0.22"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8a0d197bd2c9dc6e53b84da9556a69ba4cdfab8619eb41a8bd1cc2027a0f6b1d"
+checksum = "b39cdef0fa800fc44525c84ccb54a029961a8215f9619753635a9c0d2538d46d"
 
 [[package]]
 name = "ryu"
@@ -1683,142 +1497,29 @@ dependencies = [
 ]
 
 [[package]]
-name = "scsys"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "00fffd67a93106e087d1863df313f6f9d2d65b415bf6e684c8fb33c5b0c5cf36"
-dependencies = [
- "scsys-config",
- "scsys-core",
- "scsys-crypto",
- "scsys-derive",
- "scsys-traits",
- "scsys-util",
-]
-
-[[package]]
-name = "scsys-config"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "76a2cac05dfdbdefee1b2c9da644ec51c862fa37bef6a6611f2c89fb2f15973e"
-dependencies = [
- "anyhow",
- "config",
- "scsys-core",
- "serde",
- "serde_derive",
- "serde_json",
- "smart-default",
- "strum",
- "thiserror",
- "tracing",
- "tracing-subscriber",
- "url",
-]
-
-[[package]]
-name = "scsys-core"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "dccf5713c694fb005f4ba8bd8987cdf05da2494d1e6fe8ad8e6a48ff2564f2b9"
-dependencies = [
- "anyhow",
- "chrono",
- "getrandom",
- "num-traits",
- "paste",
- "rand 0.9.1",
- "rand_distr",
- "serde",
- "serde_derive",
- "serde_json",
- "smart-default",
- "strum",
- "thiserror",
- "time",
- "tracing",
- "uuid",
- "wasm-bindgen",
-]
-
-[[package]]
-name = "scsys-crypto"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5ea33a001aaeca8617c3622d79256c1a33065af3ac55f37db9df46229ca64a1d"
-dependencies = [
- "anyhow",
- "bincode",
- "blake3",
- "chrono",
- "digest",
- "generic-array 1.2.0",
- "getrandom",
- "paste",
- "rand 0.9.1",
- "rand_distr",
- "scsys-core",
- "serde",
- "serde_derive",
- "serde_json",
- "smart-default",
- "strum",
- "thiserror",
- "time",
- "tracing",
- "typenum",
- "uuid",
-]
-
-[[package]]
-name = "scsys-derive"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d8fb965e4c5f680530848ae90393d30a51c678fb9aba6261ccc1a2fcd487e7a0"
-dependencies = [
- "proc-macro2",
- "quote",
- "syn",
-]
-
-[[package]]
-name = "scsys-traits"
-version = "0.3.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "64cfc23268b9d518c55fab9899512bbceb513f0fd692f886d6fa3b1e88d05e98"
-dependencies = [
- "num-traits",
-]
-
-[[package]]
-name = "scsys-util"
-version = "0.3.1"
+name = "serde"
+version = "1.0.228"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "57dccdae8b4079446f05f2c2978ba316a76ab4958e20d4ee3cd2e5166258f7a2"
+checksum = "9a8e94ea7f378bd32cbbd37198a4a91436180c5bb472411e48b5ec2e2124ae9e"
 dependencies = [
- "num-traits",
- "rand 0.9.1",
- "serde",
+ "serde_core",
  "serde_derive",
- "serde_json",
- "strum",
- "tracing",
 ]
 
 [[package]]
-name = "serde"
-version = "1.0.219"
+name = "serde_core"
+version = "1.0.228"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5f0e2c6ed6606019b4e29e69dbaba95b11854410e5347d525002456dbbb786b6"
+checksum = "41d385c7d4ca58e59fc732af25c3983b67ac852c1a25000afe1175de458b67ad"
 dependencies = [
  "serde_derive",
 ]
 
 [[package]]
 name = "serde_derive"
-version = "1.0.219"
+version = "1.0.228"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5b0276cf7f2c73365f7157c8123c21cd9a50fbbd844757af28ca1f5925fc2a00"
+checksum = "d540f220d3187173da220f885ab66608367b6574e925011a9353e4badda91d79"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -1827,14 +1528,15 @@ dependencies = [
 
 [[package]]
 name = "serde_json"
-version = "1.0.140"
+version = "1.0.145"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "20068b6e96dc6c9bd23e01df8827e6c7e1f2fddd43c21810382803c136b99373"
+checksum = "402a6f66d8c709116cf22f558eab210f5a50187f702eb4d7e5ef38d9a7f1c79c"
 dependencies = [
  "itoa",
  "memchr",
  "ryu",
  "serde",
+ "serde_core",
 ]
 
 [[package]]
@@ -1859,7 +1561,7 @@ dependencies = [
  "chrono",
  "hex",
  "indexmap 1.9.3",
- "indexmap 2.10.0",
+ "indexmap 2.12.1",
  "serde",
  "serde_derive",
  "serde_json",
@@ -1894,12 +1596,6 @@ version = "1.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
 
-[[package]]
-name = "slab"
-version = "0.4.10"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "04dc19736151f35336d325007ac991178d504a119863a2fcb3758cdb5e52c50d"
-
 [[package]]
 name = "smallvec"
 version = "1.15.1"
@@ -1919,19 +1615,19 @@ dependencies = [
 
 [[package]]
 name = "socket2"
-version = "0.5.10"
+version = "0.6.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e22376abed350d73dd1cd119b57ffccad95b4e585a7cda43e286245ce23c0678"
+checksum = "17129e116933cf371d018bb80ae557e889637989d8638274fb25622827b03881"
 dependencies = [
  "libc",
- "windows-sys 0.52.0",
+ "windows-sys 0.60.2",
 ]
 
 [[package]]
 name = "stable_deref_trait"
-version = "1.2.0"
+version = "1.2.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a8f112729512f8e442d81f95a8a7ddf2b7c6b8a1a6f509a95864142b30cab2d3"
+checksum = "6ce2be8dc25455e1f91df71bfa12ad37d7af1092ae736f3a6cd0e37bc7810596"
 
 [[package]]
 name = "strength_reduce"
@@ -1947,31 +1643,30 @@ checksum = "7da8b5736845d9f2fcb837ea5d9e2628564b3b043a70948a3f0b778838c5fb4f"
 
 [[package]]
 name = "strum"
-version = "0.27.1"
+version = "0.27.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f64def088c51c9510a8579e3c5d67c65349dcf755e5479ad3d010aa6454e2c32"
+checksum = "af23d6f6c1a224baef9d3f61e287d2761385a5b88fdab4eb4c6f11aeb54c4bcf"
 dependencies = [
  "strum_macros",
 ]
 
 [[package]]
 name = "strum_macros"
-version = "0.27.1"
+version = "0.27.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c77a8c5abcaf0f9ce05d62342b7d298c346515365c36b673df4ebe3ced01fde8"
+checksum = "7695ce3845ea4b33927c055a39dc438a45b059f7c1b3d91d38d10355fb8cbca7"
 dependencies = [
  "heck",
  "proc-macro2",
  "quote",
- "rustversion",
  "syn",
 ]
 
 [[package]]
 name = "syn"
-version = "2.0.104"
+version = "2.0.111"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "17b6f705963418cdb9927482fa304bc562ece2fdd4f616084c50b7023b435a40"
+checksum = "390cc9a294ab71bdb1aa2e99d13be9c753cd2d7bd6560c77118597410c4d2e87"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2000,18 +1695,18 @@ dependencies = [
 
 [[package]]
 name = "thiserror"
-version = "2.0.12"
+version = "2.0.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "567b8a2dae586314f7be2a752ec7474332959c6460e02bde30d702a66d488708"
+checksum = "f63587ca0f12b72a0600bcba1d40081f830876000bb46dd2337a3051618f4fc8"
 dependencies = [
  "thiserror-impl",
 ]
 
 [[package]]
 name = "thiserror-impl"
-version = "2.0.12"
+version = "2.0.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7f7cf42b4507d8ea322120659672cf1b9dbb93f8f2d4ecfd6e51350ff5b17a1d"
+checksum = "3ff15c8ecd7de3849db632e14d18d2571fa09dfc5ed93479bc4485c7a517c913"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2029,13 +1724,12 @@ dependencies = [
 
 [[package]]
 name = "time"
-version = "0.3.41"
+version = "0.3.44"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8a7619e19bc266e0f9c5e6686659d394bc57973859340060a69221e57dbc0c40"
+checksum = "91e7d9e3bb61134e77bde20dd4825b97c010155709965fedf0f49bb138e52a9d"
 dependencies = [
  "deranged",
  "itoa",
- "js-sys",
  "num-conv",
  "powerfmt",
  "serde",
@@ -2045,15 +1739,15 @@ dependencies = [
 
 [[package]]
 name = "time-core"
-version = "0.1.4"
+version = "0.1.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c9e9a38711f559d9e3ce1cdb06dd7c5b8ea546bc90052da6d06bb76da74bb07c"
+checksum = "40868e7c1d2f0b8d73e4a8c7f0ff63af4f6d19be117e90bd73eb1d62cf831c6b"
 
 [[package]]
 name = "time-macros"
-version = "0.2.22"
+version = "0.2.24"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3526739392ec93fd8b359c8e98514cb3e8e021beb4e5f597b00a0221f8ed8a49"
+checksum = "30cfb0125f12d9c277f35663a0a33f8c30190f4e4574868a330595412d34ebf3"
 dependencies = [
  "num-conv",
  "time-core",
@@ -2061,9 +1755,9 @@ dependencies = [
 
 [[package]]
 name = "tinystr"
-version = "0.8.1"
+version = "0.8.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5d4f6d1145dcb577acf783d4e601bc1d76a13337bb54e6233add580b07344c8b"
+checksum = "42d3e9c45c09de15d06dd8acf5f4e0e399e85927b7f00711024eb7ae10fa4869"
 dependencies = [
  "displaydoc",
  "zerovec",
@@ -2081,18 +1775,15 @@ dependencies = [
 
 [[package]]
 name = "tokio"
-version = "1.46.0"
+version = "1.48.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1140bb80481756a8cbe10541f37433b459c5aa1e727b4c020fbfebdc25bf3ec4"
+checksum = "ff360e02eab121e0bc37a2d3b4d4dc622e6eda3a8e5253d5435ecf5bd4c68408"
 dependencies = [
- "backtrace",
- "io-uring",
  "libc",
  "mio",
  "pin-project-lite",
- "slab",
  "socket2",
- "windows-sys 0.52.0",
+ "windows-sys 0.61.2",
 ]
 
 [[package]]
@@ -2112,9 +1803,9 @@ dependencies = [
 
 [[package]]
 name = "tower-http"
-version = "0.6.6"
+version = "0.6.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "adc82fd73de2a9722ac5da747f12383d2bfdb93591ee6c58486e0097890f05f2"
+checksum = "9cf146f99d442e8e68e585f5d798ccd3cad9a7835b917e09728880a862706456"
 dependencies = [
  "bitflags",
  "bytes",
@@ -2174,15 +1865,14 @@ dependencies = [
 
 [[package]]
 name = "tracing-subscriber"
-version = "0.3.19"
+version = "0.3.20"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e8189decb5ac0fa7bc8b96b7cb9b2701d60d48805aca84a238004d665fcc4008"
+checksum = "2054a14f5307d601f88daf0553e1cbf472acc4f2c51afab632431cdcd72124d5"
 dependencies = [
  "matchers",
  "nu-ansi-term",
  "once_cell",
- "regex",
- "serde",
+ "regex-automata",
  "sharded-slab",
  "thread_local",
  "tracing",
@@ -2205,29 +1895,17 @@ version = "0.2.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "e421abadd41a4225275504ea4d6566923418b7f05506fbc9c0fe86ba7396114b"
 
-[[package]]
-name = "typenum"
-version = "1.18.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1dccffe3ce07af9386bfd29e80c0ab1a8205a2fc34e4bcd40364df902cfa8f3f"
-
 [[package]]
 name = "unicode-ident"
-version = "1.0.18"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5a5f39404a5da50712a4c1eecf25e90dd62b613502b7e925fd4e4d19b5c96512"
-
-[[package]]
-name = "unty"
-version = "0.0.4"
+version = "1.0.22"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6d49784317cd0d1ee7ec5c716dd598ec5b4483ea832a2dced265471cc0f690ae"
+checksum = "9312f7c4f6ff9069b165498234ce8be658059c6728633667c526e27dc2cf1df5"
 
 [[package]]
 name = "url"
-version = "2.5.4"
+version = "2.5.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "32f8b686cadd1473f4bd0117a5d28d36b1ade384ea9b5069a1c40aefed7fda60"
+checksum = "08bc136a29a3d1758e07a9cca267be308aeebf5cfd5a10f3f67ab2097683ef5b"
 dependencies = [
  "form_urlencoded",
  "idna",
@@ -2242,28 +1920,38 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b6c140620e7ffbb22c2dee59cafe6084a59b5ffc27a8859a5f0d494b5d52b6be"
 
 [[package]]
-name = "uuid"
-version = "1.17.0"
+name = "variants"
+version = "0.0.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3cf4199d1e5d15ddd86a694e4d0dffa9c323ce759fea589f00fef9d81cc1931d"
+checksum = "c3d2f539cc5b8d5442f7558e2981adabd7462d6f318df8a5a12860a7242587e3"
 dependencies = [
- "getrandom",
- "js-sys",
- "serde",
- "wasm-bindgen",
+ "anyhow",
+ "thiserror",
+ "variants-derive",
+ "variants-macros",
 ]
 
 [[package]]
-name = "version_check"
-version = "0.9.5"
+name = "variants-derive"
+version = "0.0.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
+checksum = "def932f16e8fac8b72d08953f57f081006c7006fac129d2aff1e4bebbbcfe9ab"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn",
+]
 
 [[package]]
-name = "virtue"
-version = "0.0.18"
+name = "variants-macros"
+version = "0.0.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "051eb1abcf10076295e815102942cc58f9d5e3b4560e46e53c21e8ff6f3af7b1"
+checksum = "c2bd5a945ea1267baa1c77d70e626e8c0268818d0edc1f1671f11def7e6708b4"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn",
+]
 
 [[package]]
 name = "walkdir"
@@ -2291,45 +1979,32 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ccf3ec651a847eb01de73ccad15eb7d99f80485de043efb2f370cd654f4ea44b"
 
 [[package]]
-name = "wasi"
-version = "0.14.2+wasi-0.2.4"
+name = "wasip2"
+version = "1.0.1+wasi-0.2.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9683f9a5a998d873c0d21fcbe3c083009670149a8fab228644b8bd36b2c48cb3"
+checksum = "0562428422c63773dad2c345a1882263bbf4d65cf3f42e90921f787ef5ad58e7"
 dependencies = [
- "wit-bindgen-rt",
+ "wit-bindgen",
 ]
 
 [[package]]
 name = "wasm-bindgen"
-version = "0.2.100"
+version = "0.2.105"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1edc8929d7499fc4e8f0be2262a241556cfc54a0bea223790e71446f2aab1ef5"
+checksum = "da95793dfc411fbbd93f5be7715b0578ec61fe87cb1a42b12eb625caa5c5ea60"
 dependencies = [
  "cfg-if",
  "once_cell",
  "rustversion",
  "wasm-bindgen-macro",
-]
-
-[[package]]
-name = "wasm-bindgen-backend"
-version = "0.2.100"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2f0a0651a5c2bc21487bde11ee802ccaf4c51935d0d3d42a6101f98161700bc6"
-dependencies = [
- "bumpalo",
- "log",
- "proc-macro2",
- "quote",
- "syn",
  "wasm-bindgen-shared",
 ]
 
 [[package]]
 name = "wasm-bindgen-futures"
-version = "0.4.50"
+version = "0.4.55"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "555d470ec0bc3bb57890405e5d4322cc9ea83cebb085523ced7be4144dac1e61"
+checksum = "551f88106c6d5e7ccc7cd9a16f312dd3b5d36ea8b4954304657d5dfba115d4a0"
 dependencies = [
  "cfg-if",
  "js-sys",
@@ -2340,9 +2015,9 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-macro"
-version = "0.2.100"
+version = "0.2.105"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7fe63fc6d09ed3792bd0897b314f53de8e16568c2b3f7982f468c0bf9bd0b407"
+checksum = "04264334509e04a7bf8690f2384ef5265f05143a4bff3889ab7a3269adab59c2"
 dependencies = [
  "quote",
  "wasm-bindgen-macro-support",
@@ -2350,22 +2025,22 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-macro-support"
-version = "0.2.100"
+version = "0.2.105"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8ae87ea40c9f689fc23f209965b6fb8a99ad69aeeb0231408be24920604395de"
+checksum = "420bc339d9f322e562942d52e115d57e950d12d88983a14c79b86859ee6c7ebc"
 dependencies = [
+ "bumpalo",
  "proc-macro2",
  "quote",
  "syn",
- "wasm-bindgen-backend",
  "wasm-bindgen-shared",
 ]
 
 [[package]]
 name = "wasm-bindgen-shared"
-version = "0.2.100"
+version = "0.2.105"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1a05d73b933a847d6cccdda8f838a22ff101ad9bf93e33684f39c1f5f0eece3d"
+checksum = "76f218a38c84bcb33c25ec7059b07847d465ce0e0a76b995e134a45adcb6af76"
 dependencies = [
  "unicode-ident",
 ]
@@ -2383,50 +2058,28 @@ dependencies = [
 
 [[package]]
 name = "web-sys"
-version = "0.3.77"
+version = "0.3.82"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "33b6dd2ef9186f1f2072e409e99cd22a975331a6b3591b12c764e0e55c60d5d2"
+checksum = "3a1f95c0d03a47f4ae1f7a64643a6bb97465d9b740f0fa8f90ea33915c99a9a1"
 dependencies = [
  "js-sys",
  "wasm-bindgen",
 ]
 
-[[package]]
-name = "winapi"
-version = "0.3.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5c839a674fcd7a98952e593242ea400abe93992746761e38641405d28b00f419"
-dependencies = [
- "winapi-i686-pc-windows-gnu",
- "winapi-x86_64-pc-windows-gnu",
-]
-
-[[package]]
-name = "winapi-i686-pc-windows-gnu"
-version = "0.4.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ac3b87c63620426dd9b991e5ce0329eff545bccbbb34f3be09ff6fb6ab51b7b6"
-
 [[package]]
 name = "winapi-util"
-version = "0.1.9"
+version = "0.1.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cf221c93e13a30d793f7645a0e7762c55d169dbb0a49671918a2319d289b10bb"
+checksum = "c2a7b1c03c876122aa43f3020e6c3c3ee5c05081c9a00739faf7503aeba10d22"
 dependencies = [
- "windows-sys 0.59.0",
+ "windows-sys 0.61.2",
 ]
 
-[[package]]
-name = "winapi-x86_64-pc-windows-gnu"
-version = "0.4.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "712e227841d057c1ee1cd2fb22fa7e5a5461ae8e48fa2ca79ec42cfc1931183f"
-
 [[package]]
 name = "windows-core"
-version = "0.61.2"
+version = "0.62.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c0fdd3ddb90610c7638aa2b3a3ab2904fb9e5cdbecc643ddb3647212781c4ae3"
+checksum = "b8e83a14d34d0623b51dce9581199302a221863196a1dde71a7663a4c2be9deb"
 dependencies = [
  "windows-implement",
  "windows-interface",
@@ -2437,9 +2090,9 @@ dependencies = [
 
 [[package]]
 name = "windows-implement"
-version = "0.60.0"
+version = "0.60.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a47fddd13af08290e67f4acabf4b459f647552718f683a7b415d290ac744a836"
+checksum = "053e2e040ab57b9dc951b72c264860db7eb3b0200ba345b4e4c3b14f67855ddf"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2448,9 +2101,9 @@ dependencies = [
 
 [[package]]
 name = "windows-interface"
-version = "0.59.1"
+version = "0.59.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bd9211b69f8dcdfa817bfd14bf1c97c9188afa36f4750130fcdf3f400eca9fa8"
+checksum = "3f316c4a2570ba26bbec722032c4099d8c8bc095efccdc15688708623367e358"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2459,52 +2112,53 @@ dependencies = [
 
 [[package]]
 name = "windows-link"
-version = "0.1.3"
+version = "0.2.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5e6ad25900d524eaabdbbb96d20b4311e1e7ae1699af4fb28c17ae66c80d798a"
+checksum = "f0805222e57f7521d6a62e36fa9163bc891acd422f971defe97d64e70d0a4fe5"
 
 [[package]]
 name = "windows-result"
-version = "0.3.4"
+version = "0.4.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "56f42bd332cc6c8eac5af113fc0c1fd6a8fd2aa08a0119358686e5160d0586c6"
+checksum = "7781fa89eaf60850ac3d2da7af8e5242a5ea78d1a11c49bf2910bb5a73853eb5"
 dependencies = [
  "windows-link",
 ]
 
 [[package]]
 name = "windows-strings"
-version = "0.4.2"
+version = "0.5.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "56e6c93f3a0c3b36176cb1327a4958a0353d5d166c2a35cb268ace15e91d3b57"
+checksum = "7837d08f69c77cf6b07689544538e017c1bfcf57e34b4c0ff58e6c2cd3b37091"
 dependencies = [
  "windows-link",
 ]
 
 [[package]]
 name = "windows-sys"
-version = "0.52.0"
+version = "0.60.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "282be5f36a8ce781fad8c8ae18fa3f9beff57ec1b52cb3de0789201425d9a33d"
+checksum = "f2f500e4d28234f72040990ec9d39e3a6b950f9f22d3dba18416c35882612bcb"
 dependencies = [
  "windows-targets",
 ]
 
 [[package]]
 name = "windows-sys"
-version = "0.59.0"
+version = "0.61.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1e38bc4d79ed67fd075bcc251a1c39b32a1776bbe92e5bef1f0bf1f8c531853b"
+checksum = "ae137229bcbd6cdf0f7b80a31df61766145077ddf49416a728b02cb3921ff3fc"
 dependencies = [
- "windows-targets",
+ "windows-link",
 ]
 
 [[package]]
 name = "windows-targets"
-version = "0.52.6"
+version = "0.53.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9b724f72796e036ab90c1021d4780d4d3d648aca59e491e6b98e725b84e99973"
+checksum = "4945f9f551b88e0d65f3db0bc25c33b8acea4d9e41163edf90dcd0b19f9069f3"
 dependencies = [
+ "windows-link",
  "windows_aarch64_gnullvm",
  "windows_aarch64_msvc",
  "windows_i686_gnu",
@@ -2517,83 +2171,70 @@ dependencies = [
 
 [[package]]
 name = "windows_aarch64_gnullvm"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "32a4622180e7a0ec044bb555404c800bc9fd9ec262ec147edd5989ccd0c02cd3"
+checksum = "a9d8416fa8b42f5c947f8482c43e7d89e73a173cead56d044f6a56104a6d1b53"
 
 [[package]]
 name = "windows_aarch64_msvc"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "09ec2a7bb152e2252b53fa7803150007879548bc709c039df7627cabbd05d469"
+checksum = "b9d782e804c2f632e395708e99a94275910eb9100b2114651e04744e9b125006"
 
 [[package]]
 name = "windows_i686_gnu"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8e9b5ad5ab802e97eb8e295ac6720e509ee4c243f69d781394014ebfe8bbfa0b"
+checksum = "960e6da069d81e09becb0ca57a65220ddff016ff2d6af6a223cf372a506593a3"
 
 [[package]]
 name = "windows_i686_gnullvm"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0eee52d38c090b3caa76c563b86c3a4bd71ef1a819287c19d586d7334ae8ed66"
+checksum = "fa7359d10048f68ab8b09fa71c3daccfb0e9b559aed648a8f95469c27057180c"
 
 [[package]]
 name = "windows_i686_msvc"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "240948bc05c5e7c6dabba28bf89d89ffce3e303022809e73deaefe4f6ec56c66"
+checksum = "1e7ac75179f18232fe9c285163565a57ef8d3c89254a30685b57d83a38d326c2"
 
 [[package]]
 name = "windows_x86_64_gnu"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "147a5c80aabfbf0c7d901cb5895d1de30ef2907eb21fbbab29ca94c5b08b1a78"
+checksum = "9c3842cdd74a865a8066ab39c8a7a473c0778a3f29370b5fd6b4b9aa7df4a499"
 
 [[package]]
 name = "windows_x86_64_gnullvm"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "24d5b23dc417412679681396f2b49f3de8c1473deb516bd34410872eff51ed0d"
+checksum = "0ffa179e2d07eee8ad8f57493436566c7cc30ac536a3379fdf008f47f6bb7ae1"
 
 [[package]]
 name = "windows_x86_64_msvc"
-version = "0.52.6"
+version = "0.53.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
+checksum = "d6bbff5f0aada427a1e5a6da5f1f98158182f26556f345ac9e04d36d0ebed650"
 
 [[package]]
-name = "winnow"
-version = "0.7.11"
+name = "wit-bindgen"
+version = "0.46.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "74c7b26e3480b707944fc872477815d29a8e429d2f93a1ce000f5fa84a15cbcd"
-dependencies = [
- "memchr",
-]
-
-[[package]]
-name = "wit-bindgen-rt"
-version = "0.39.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6f42320e61fe2cfd34354ecb597f86f413484a798ba44a8ca1165c58d42da6c1"
-dependencies = [
- "bitflags",
-]
+checksum = "f17a85883d4e6d00e8a97c586de764dabcc06133f7f1d55dce5cdc070ad7fe59"
 
 [[package]]
 name = "writeable"
-version = "0.6.1"
+version = "0.6.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ea2f10b9bb0928dfb1b42b65e1f9e36f7f54dbdf08457afefb38afcdec4fa2bb"
+checksum = "9edde0db4769d2dc68579893f2306b26c6ecfbe0ef499b013d731b7b9247e0b9"
 
 [[package]]
 name = "yoke"
-version = "0.8.0"
+version = "0.8.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5f41bb01b8226ef4bfd589436a297c53d118f65921786300e427be8d487695cc"
+checksum = "72d6e5c6afb84d73944e5cedb052c4680d5657337201555f9f2a16b7406d4954"
 dependencies = [
- "serde",
  "stable_deref_trait",
  "yoke-derive",
  "zerofrom",
@@ -2601,9 +2242,9 @@ dependencies = [
 
 [[package]]
 name = "yoke-derive"
-version = "0.8.0"
+version = "0.8.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "38da3c9736e16c5d3c8c597a9aaa5d1fa565d0532ae05e27c24aa62fb32c0ab6"
+checksum = "b659052874eb698efe5b9e8cf382204678a0086ebf46982b79d6ca3182927e5d"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2613,18 +2254,18 @@ dependencies = [
 
 [[package]]
 name = "zerocopy"
-version = "0.8.26"
+version = "0.8.30"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1039dd0d3c310cf05de012d8a39ff557cb0d23087fd44cad61df08fc31907a2f"
+checksum = "4ea879c944afe8a2b25fef16bb4ba234f47c694565e97383b36f3a878219065c"
 dependencies = [
  "zerocopy-derive",
 ]
 
 [[package]]
 name = "zerocopy-derive"
-version = "0.8.26"
+version = "0.8.30"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ecf5b4cc5364572d7f4c329661bcc82724222973f2cab6f050a4e5c22f75181"
+checksum = "cf955aa904d6040f70dc8e9384444cb1030aed272ba3cb09bbc4ab9e7c1f34f5"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2654,9 +2295,9 @@ dependencies = [
 
 [[package]]
 name = "zerotrie"
-version = "0.2.2"
+version = "0.2.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "36f0bbd478583f79edad978b407914f61b2972f5af6fa089686016be8f9af595"
+checksum = "2a59c17a5562d507e4b54960e8569ebee33bee890c70aa3fe7b97e85a9fd7851"
 dependencies = [
  "displaydoc",
  "yoke",
@@ -2665,9 +2306,9 @@ dependencies = [
 
 [[package]]
 name = "zerovec"
-version = "0.11.2"
+version = "0.11.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4a05eb080e015ba39cc9e23bbe5e7fb04d5fb040350f99f34e338d5fdd294428"
+checksum = "6c28719294829477f525be0186d13efa9a3c602f7ec202ca9e353d310fb9a002"
 dependencies = [
  "yoke",
  "zerofrom",
@@ -2676,9 +2317,9 @@ dependencies = [
 
 [[package]]
 name = "zerovec-derive"
-version = "0.11.1"
+version = "0.11.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5b96237efa0c878c64bd89c436f661be4e46b2f3eff1ebb976f7ef2321d2f58f"
+checksum = "eadce39539ca5cb3985590102671f2567e659fca9666581ad3411d59207951f3"
 dependencies = [
  "proc-macro2",
  "quote",
diff --git a/Cargo.toml b/Cargo.toml
index fce34071..0029123c 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -1,72 +1,59 @@
 [workspace]
-default-members = [
-    "concision"
-]
+default-members = ["concision"]
 members = [
-    "concision",
-    "core",
-    "data",
-    "derive",
-    "init",
-    "macros",
-    "neural",
-    "utils",
-    "ext",
-    "models/*",
+  "concision", 
+  "core", 
+  "data", 
+  "derive", 
+  "ext", 
+  "init", 
+  "macros", 
+  "neural", 
+  "params", 
+  "traits",
+  "utils",
+  "models/*", 
 ]
 resolver = "3"
 
 [workspace.package]
-authors = [
-    "FL03 <jo3mccain@icloud.com> (https://github.com/FL03)",
-    "Scattered-Systems <support@scsys.io> (https://github.com/scattered-systems)"
-]
-categories = [
-    "algorithms",
-    "mathematics",
-    "science"
-]
+authors = ["FL03 <jo3mccain@icloud.com> (https://github.com/FL03)", "Scattered-Systems <support@scsys.io> (https://github.com/scattered-systems)"]
+categories = ["algorithms", "mathematics", "science"]
 description = "Concision is a toolkit for designing machine-learning models in Rust."
 edition = "2024"
 homepage = "https://github.com/FL03/concision/wiki"
-keywords = [
-    "data-science",
-    "machine-learning",
-    "scsys",
-    "toolkit"
-]
+keywords = ["data-science", "machine-learning", "scsys", "toolkit"]
 license = "Apache-2.0"
 readme = "README.md"
 repository = "https://github.com/FL03/concision.git"
 rust-version = "1.85.0"
-version = "0.2.7"
+version = "0.2.8"
 
 [workspace.dependencies]
-concision = { default-features = false, path = "concision", version = "0.2.7" }
-concision-core = { default-features = false, path = "core", version = "0.2.7" }
-concision-data = { default-features = false, path = "data", version = "0.2.7" }
-concision-derive = { default-features = false, path = "derive", version = "0.2.7" }
-concision-init = { default-features = false, path = "init", version = "0.2.7" }
-concision-macros = { default-features = false, path = "macros", version = "0.2.7" }
-concision-neural = { default-features = false, path = "neural", version = "0.2.7" }
-concision-utils = { default-features = false, path = "utils", version = "0.2.7" }
+concision = { default-features = false, path = "concision", version = "0.2.8" }
+
+concision-core = { default-features = false, path = "core", version = "0.2.8" }
+concision-data = { default-features = false, path = "data", version = "0.2.8" }
+concision-derive = { default-features = false, path = "derive", version = "0.2.8" }
+concision-init = { default-features = false, path = "init", version = "0.2.8" }
+concision-macros = { default-features = false, path = "macros", version = "0.2.8" }
+concision-neural = { default-features = false, path = "neural", version = "0.2.8" }
+concision-params = { default-features = false, path = "params", version = "0.2.8" }
+concision-traits = { default-features = false, path = "traits", version = "0.2.8" }
+concision-utils = { default-features = false, path = "utils", version = "0.2.8" }
 # extras
-concision-ext = { default-features = false, path = "ext", version = "0.2.7" }
+concision-ext = { default-features = false, path = "ext", version = "0.2.8" }
 # models
-concision-models = { default-features = false, path = "macros", version = "0.2.7" }
-concision-kan = { default-features = false, path = "models/kan", version = "0.2.7" }
-concision-s4 = { default-features = false, path = "models/s4", version = "0.2.7" }
-concision-transformer = { default-features = false, path = "models/transformer", version = "0.2.7" }
+concision-kan = { default-features = false, path = "models/kan", version = "0.2.8" }
+concision-models = { default-features = false, path = "models/models", version = "0.2.8" }
+concision-s4 = { default-features = false, path = "models/s4", version = "0.2.8" }
+concision-snn = { default-features = false, path = "models/snn", version = "0.2.8" }
+concision-transformer = { default-features = false, path = "models/transformer", version = "0.2.8" }
 
 # custom
-ndtensor = { default-features = false, version = "0.1.1" }
-scsys = { default-features = false, features = ["derive"], version = "0.3.1" }
-scsys-derive = { default-features = false, version = "0.3.1" }
-# async
-futures = { default-features = false, version = "0.3" }
-tokio = { default-features = false, version = "1" }
+variants = { default-features = false, features = ["derive"], version = "0.0.1" }
 # benchmarking
-criterion = { version = "0.6" }
+criterion = { version = "0.7" }
 # concurrency & parallelism
 crossbeam = { default-features = false, version = "0.8" }
 rayon = { default-features = false, version = "1" }
@@ -76,8 +63,8 @@ serde_derive = { default-features = false, version = "1" }
 serde_json = { default-features = false, version = "1" }
 # math
 approx = { version = "0.5" }
-ndarray = { default-features = false, version = "0.16" }
-ndarray-linalg = { default-features = false, version = "0.17" }
+ndarray = { default-features = false, version = "0.17" }
+ndarray-linalg = { default-features = false, version = "0.18" }
 ndarray-stats = "0.6"
 num = { default-features = false, version = "0.4" }
 num-complex = { default-features = false, version = "0.4" }
diff --git a/concision/Cargo.toml b/concision/Cargo.toml
index ca106362..6f053c2a 100644
--- a/concision/Cargo.toml
+++ b/concision/Cargo.toml
@@ -14,27 +14,52 @@ repository.workspace = true
 rust-version.workspace = true
 version.workspace = true
 
-[package.metadata.docs.rs]
-all-features = false
-doc-scrape-examples = true
-features = ["full"]
-rustc-args = ["--cfg", "docsrs"]
-version = "v{{version}}"
-
-[package.metadata.release]
-no-dev-version = true
-tag-name = "{{version}}"
-
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib"
-]
+crate-type = ["cdylib", "rlib"]
+
 bench = true
 doc = true
 doctest = true
 test = true
 
+# ************* [Benchmarks] *************
+[[bench]]
+harness = false
+name = "default"
+path = "benches/default.rs"
+required-features = ["std"]
+
+[[bench]]
+harness = false
+name = "params"
+path = "benches/params.rs"
+required-features = [
+  "neural",
+  "approx",
+  "rand",
+  "std",
+  "tracing",
+]
+
+# ************* [Examples] *************
+[[example]]
+name = "basic"
+required-features = [
+  "approx",
+  "rand",
+  "std",
+  "tracing",
+]
+
+# ************* [Unit Tests] *************
+[[test]]
+name = "default"
+
+[[test]]
+name = "simple"
+path = "tests/simple/main.rs"
+required-features = ["approx", "default", "neural", "rand"]
+
 [dependencies]
 concision-core = { workspace = true }
 concision-data = { optional = true, workspace = true }
@@ -43,7 +68,7 @@ concision-macros = { optional = true, workspace = true }
 concision-neural = { optional = true, workspace = true }
 
 [dev-dependencies]
-anyhow = { workspace = true }
+anyhow = { features = ["std"], workspace = true }
 approx = { workspace = true }
 criterion = { features = ["plotters"], workspace = true }
 lazy_static = { workspace = true }
@@ -55,28 +80,27 @@ tracing-subscriber = { workspace = true }
 
 [features]
 default = [
-    "data",
-    "neural",
-    "std",
-    "utils",
+  "data",
+  "neural",
+  "std",
+  "utils",
 ]
 
 full = [
-    "default",
-    "anyhow",
-    "approx",
-    "data",
-    "derive",
-    "macros",
-    "rand",
-    "serde",
-    "tracing"
+  "default",
+  "approx",
+  "data",
+  "derive",
+  "macros",
+  "rand",
+  "serde",
+  "tracing"
 ]
 
 nightly = [
-    "concision-core/nightly",
-    "concision-data?/nightly",
-    "concision-neural?/nightly",
+  "concision-core/nightly",
+  "concision-data?/nightly",
+  "concision-neural?/nightly",
 ]
 
 # ************* [FF:Features] *************
@@ -88,106 +112,95 @@ data = ["dep:concision-data"]
 
 init = ["concision-core/init"]
 
-neural = [
-    "dep:concision-neural",
-    "alloc",
-]
+neural = ["dep:concision-neural", "alloc"]
 
-utils = [
-    "concision-core/utils"
-]
+utils = ["concision-core/utils"]
 
 # ************* [FF:Environments] *************
 std = [
-    "alloc",
-    "concision-core/std",
-    "concision-data?/std",
-    "concision-neural?/std",
+  "alloc",
+  "concision-core/std",
+  "concision-data?/std",
+  "concision-neural?/std",
 ]
 
 wasi = [
-    "concision-core/wasi",
-    "concision-data?/wasi",
-    "concision-neural?/wasi"
+  "concision-core/wasi",
+  "concision-data?/wasi",
+  "concision-neural?/wasi"
 ]
 
 wasm = [
-    "concision-core/wasm",
-    "concision-data?/wasm",
-    "concision-neural?/wasm"
+  "concision-core/wasm",
+  "concision-data?/wasm",
+  "concision-neural?/wasm"
 ]
 
 # ************* [FF:Dependencies] *************
 alloc = [
-    "concision-core/alloc",
-    "concision-data?/alloc",
-    "concision-neural?/alloc",
-]
-
-anyhow = [
-    "concision-core/anyhow",
-    "concision-data?/anyhow",
-    "concision-neural?/anyhow",
+  "concision-core/alloc",
+  "concision-data?/alloc",
+  "concision-neural?/alloc",
 ]
 
 approx = [
-    "concision-core/approx",
-    "concision-data?/approx",
-    "concision-neural?/approx"
+  "concision-core/approx",
+  "concision-data?/approx",
+  "concision-neural?/approx"
 ]
 
 complex = [
-    "concision-core/complex",
-    "concision-data?/complex",
-    "concision-neural?/complex"
+  "concision-core/complex",
+  "concision-data?/complex",
+  "concision-neural?/complex"
 ]
 
 json = [
-    "concision-core/json",
-    "concision-data?/json",
-    "concision-neural?/json"
+  "concision-core/json",
+  "concision-data?/json",
+  "concision-neural?/json"
 ]
 
 rand = [
-    "concision-core/rand",
-    "concision-data?/rand",
-    "concision-neural?/rand"
+  "concision-core/rand",
+  "concision-data?/rand",
+  "concision-neural?/rand"
 ]
 
 rng = [
-    "concision-core/rng",
-    "concision-data?/rng",
-    "concision-neural?/rng"
+  "concision-core/rng",
+  "concision-data?/rng",
+  "concision-neural?/rng"
 ]
 
 rayon = [
-    "concision-core/rayon",
-    "concision-data?/rayon",
-    "concision-neural?/rayon"
+  "concision-core/rayon",
+  "concision-data?/rayon",
+  "concision-neural?/rayon"
 ]
 
 rustfft = [
-    "concision-core/rustfft",
-    "concision-neural?/rustfft"
+  "concision-core/rustfft",
+  "concision-neural?/rustfft"
 ]
 
 serde = [
-    "concision-core/serde",
-    "concision-data?/serde",
-    "concision-neural?/serde"
+  "concision-core/serde",
+  "concision-data?/serde",
+  "concision-neural?/serde"
 ]
 
 tracing = [
-    "concision-core/tracing",
-    "concision-data?/tracing",
-    "concision-neural?/tracing"
+  "concision-core/tracing",
+  "concision-data?/tracing",
+  "concision-neural?/tracing"
 ]
 
 # ********* [FF] Blas *********
 blas = [
-    "concision-core/blas",
-    "concision-data?/blas",
-    "concision-neural?/blas"
+  "concision-core/blas",
+  "concision-data?/blas",
+  "concision-neural?/blas"
 ]
 
 intel-mkl-system = ["blas"]
@@ -202,40 +215,14 @@ openblas-system = ["blas"]
 
 openblas-static = ["blas"]
 
-# ************* [Benchmarks] *************
-[[bench]]
-harness = false
-name = "default"
-path = "benches/default.rs"
-required-features = ["std"]
-
-[[bench]]
-harness = false
-name = "params"
-path = "benches/params.rs"
-required-features = [
-    "neural",
-    "approx",
-    "rand",
-    "std",
-    "tracing",
-]
-
-# ************* [Examples] *************
-[[example]]
-name = "basic"
-required-features = [
-    "approx",
-    "rand",
-    "std",
-    "tracing",
-]
-
-# ************* [Unit Tests] *************
-[[test]]
-name = "default"
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+doc-scrape-examples = true
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
 
-[[test]]
-name = "simple"
-path = "tests/simple/main.rs"
-required-features = ["approx", "default", "neural", "rand"]
\ No newline at end of file
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
diff --git a/concision/examples/basic.rs b/concision/examples/basic.rs
index f2acc4c8..15e54089 100644
--- a/concision/examples/basic.rs
+++ b/concision/examples/basic.rs
@@ -33,7 +33,7 @@ fn main() -> anyhow::Result<()> {
     assert_eq!(params.bias().shape(), &[n]);
     tracing::info!("Randomized parameters: {params:?}");
 
-    let y = params.forward(&inputs)?;
+    let y = params.forward(&inputs).expect("forward pass failed");
     assert_eq!(y.shape(), &[n]);
     tracing::info!("Forward pass: {y:?}");
 
diff --git a/concision/tests/simple/main.rs b/concision/tests/simple/main.rs
index 74783f12..cb5754f3 100644
--- a/concision/tests/simple/main.rs
+++ b/concision/tests/simple/main.rs
@@ -47,7 +47,7 @@ fn test_simple_model() -> anyhow::Result<()> {
     let expected = Array1::from_elem(model.layout().output(), 0.5);
 
     // forward the input through the model
-    let output = model.predict(&input)?;
+    let output = model.predict(&input).expect("prediction failed");
     // verify the output shape
     assert_eq!(output.dim(), (features.output()));
     // compare the results to what we expected
diff --git a/concision/tests/simple/model.rs b/concision/tests/simple/model.rs
index 923c526f..ace1d77d 100644
--- a/concision/tests/simple/model.rs
+++ b/concision/tests/simple/model.rs
@@ -2,7 +2,7 @@
     appellation: model <test>
     authors: @FL03
 */
-use cnc::nn::{DeepModelParams, Model, ModelError, ModelFeatures, StandardModelConfig, Train};
+use cnc::nn::{DeepModelParams, Model, ModelFeatures, NeuralError, StandardModelConfig, Train};
 use cnc::{Forward, Norm, Params, ReLU, Sigmoid};
 
 use ndarray::prelude::*;
@@ -65,7 +65,7 @@ where
 {
     type Output = Array<A, D>;
 
-    fn forward(&self, input: &ArrayBase<S, D>) -> cnc::Result<Self::Output> {
+    fn forward(&self, input: &ArrayBase<S, D>) -> Option<Self::Output> {
         let mut output = self
             .params()
             .input()
@@ -79,7 +79,7 @@ where
             .params()
             .output()
             .forward_then(&output, |y| y.sigmoid())?;
-        Ok(y)
+        Some(y)
     }
 }
 
@@ -99,12 +99,12 @@ where
         &mut self,
         input: &ArrayBase<S, Ix1>,
         target: &ArrayBase<T, Ix1>,
-    ) -> Result<Self::Output, ModelError> {
+    ) -> Result<Self::Output, NeuralError> {
         if input.len() != self.layout().input() {
-            return Err(ModelError::InvalidInputShape);
+            return Err(NeuralError::InvalidInputShape);
         }
         if target.len() != self.layout().output() {
-            return Err(ModelError::InvalidOutputShape);
+            return Err(NeuralError::InvalidOutputShape);
         }
         // get the learning rate from the model's configuration
         let lr = self
@@ -121,15 +121,28 @@ where
         let mut activations = Vec::new();
         activations.push(input.to_owned());
 
-        let mut output = self.params().input().forward(&input)?.relu();
+        let mut output = self
+            .params()
+            .input()
+            .forward(&input)
+            .expect("Failed to complete the forward pass for the input layer")
+            .relu();
         activations.push(output.to_owned());
         // collect the activations of the hidden
         for layer in self.params().hidden() {
-            output = layer.forward(&output)?.relu();
+            output = layer
+                .forward(&output)
+                .expect("failed to complete the forward pass for the hidden layer")
+                .relu();
             activations.push(output.to_owned());
         }
 
-        output = self.params().output().forward(&output)?.sigmoid();
+        output = self
+            .params()
+            .output()
+            .forward(&output)
+            .expect("Output layer failed to forward propagate")
+            .sigmoid();
         activations.push(output.to_owned());
 
         // Calculate output layer error
@@ -143,7 +156,8 @@ where
         // Update output weights
         self.params_mut()
             .output_mut()
-            .backward(activations.last().unwrap(), &delta, lr)?;
+            .backward(activations.last().unwrap(), &delta, lr)
+            .expect("Output failed training...");
 
         let num_hidden = self.layout().layers();
         // Iterate through hidden layers in reverse order
@@ -159,7 +173,9 @@ where
             };
             // Normalize delta to prevent exploding gradients
             delta /= delta.l2_norm();
-            self.params_mut().hidden_mut()[i].backward(&activations[i + 1], &delta, lr)?;
+            self.params_mut().hidden_mut()[i]
+                .backward(&activations[i + 1], &delta, lr)
+                .expect("Hidden failed training...");
         }
         /*
             Backpropagate to the input layer
@@ -172,7 +188,8 @@ where
         delta /= delta.l2_norm(); // Normalize the delta to prevent exploding gradients
         self.params_mut()
             .input_mut()
-            .backward(&activations[1], &delta, lr)?;
+            .backward(&activations[1], &delta, lr)
+            .expect("failed to backpropagate input layer during training...");
 
         Ok(loss)
     }
@@ -200,15 +217,15 @@ where
         &mut self,
         input: &ArrayBase<S, Ix2>,
         target: &ArrayBase<T, Ix2>,
-    ) -> Result<Self::Output, ModelError> {
+    ) -> Result<Self::Output, NeuralError> {
         if input.nrows() == 0 || target.nrows() == 0 {
-            return Err(ModelError::InvalidBatchSize);
+            return Err(NeuralError::InvalidBatchSize);
         }
         if input.ncols() != self.layout().input() {
-            return Err(ModelError::InvalidInputShape);
+            return Err(NeuralError::InvalidInputShape);
         }
         if target.ncols() != self.layout().output() || target.nrows() != input.nrows() {
-            return Err(ModelError::InvalidOutputShape);
+            return Err(NeuralError::InvalidOutputShape);
         }
         let batch_size = input.nrows();
         let mut loss = A::zero();
diff --git a/core/Cargo.toml b/core/Cargo.toml
index d1fd4840..f46649a4 100644
--- a/core/Cargo.toml
+++ b/core/Cargo.toml
@@ -25,10 +25,7 @@ no-dev-version = true
 tag-name = "{{version}}"
 
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
+crate-type = ["cdylib", "rlib"]
 bench = false
 doc = true
 doctest = true
@@ -36,12 +33,12 @@ test = true
 
 [dependencies]
 #  local
-concision-init = { optional = true, workspace = true }
+concision-init = { workspace = true }
+concision-params = { workspace = true }
+concision-traits = { workspace = true }
 concision-utils = {  optional = true, workspace = true }
 # custom
-ndtensor = { workspace = true }
-scsys = { workspace = true }
-scsys-derive = { workspace = true }
+variants = { workspace = true }
 # concurrency & parallelism
 rayon = { optional = true, workspace = true }
 # data & serialization
@@ -49,7 +46,6 @@ serde = { features = ["derive"], optional = true, workspace = true }
 serde_derive = { optional = true, workspace = true }
 serde_json = { optional = true, workspace = true }
 # error-handling
-anyhow = { optional = true, workspace = true }
 thiserror = { workspace = true }
 # logging
 tracing = { optional = true, workspace = true }
@@ -73,183 +69,162 @@ rand_distr = { optional = true, workspace = true }
 lazy_static = { workspace = true }
 
 [features]
-default = [
-    "std",
-    "utils",
-]
+default = ["std", "utils"]
 
 full = [
-    "default",
-    "anyhow",
-    "approx",
-    "complex",
-    "init",
-    "json",
-    "rand",
-    "serde",
-    "tracing",
+  "default",
+  "approx",
+  "complex",
+  "init",
+  "json",
+  "rand",
+  "serde",
+  "signal",
+  "tracing",
 ]
 
 nightly = [
-    "concision-init?/nightly",
-    "ndtensor/nightly",
-    "concision-utils?/nightly",
+  "concision-init/nightly",
+  "concision-params/nightly",
+  "concision-traits/nightly",
+  "concision-utils?/nightly",
 ]
 
 # ************* [FF:Features] *************
 init = [
-    "cnc_init",
-    "rand",
+  "rand",
 ]
 
-json = [
-    "alloc",
-    "serde",
-    "serde_json",
-    "scsys/json",
-    "ndtensor/json",
-]
+json = ["alloc", "serde", "serde_json"]
 
 signal =[
-    "complex",
-    "concision-utils?/signal",
-    "rustfft",
+  "complex",
+  "concision-utils?/signal",
+  "rustfft",
 ]
 
-utils = [
-    "cnc_utils",
-]
+utils = ["concision_utils"]
 
-cnc_init = ["dep:concision-init"]
-
-cnc_utils = ["dep:concision-utils"]
+concision_utils = ["dep:concision-utils"]
 
 # ************* [FF:Dependencies] *************
 std = [
-    "alloc",
-    "anyhow?/std",
-    "concision-init?/std",
-    "concision-utils?/std",
-    "ndarray/std",
-    "ndtensor/std",
-    "num/std",
-    "num-complex?/std",
-    "num-traits/std",
-    "rand?/std",
-    "rand?/std_rng",
-    "serde/std",
-    "scsys/std",
-    "strum/std",
-    "thiserror/std",
-    "tracing?/std",
+  "alloc",
+  "concision-init/std",
+  "concision-params/std",
+  "concision-traits/std",
+  "concision-utils?/std",
+  "ndarray/std",
+  "num/std",
+  "num-complex?/std",
+  "num-traits/std",
+  "rand?/std",
+  "rand?/std_rng",
+  "serde/std",
+  "strum/std",
+  "thiserror/std",
+  "tracing?/std",
+  "variants/std",
 ]
 
 wasi = [
-    "concision-init?/wasi",
-    "concision-utils?/wasi",
-    "ndtensor/wasi",
-    "scsys/wasi",
+  "concision-init/wasi",
+  "concision-params/wasi",
+  "concision-traits/wasi",
+  "concision-utils?/wasi",
 ]
 
 wasm = [
-    "getrandom?/wasm_js",
-    "concision-init?/wasm",
-    "concision-utils?/wasm",
-    "ndtensor/wasm",
-    "scsys/wasm",
+  "getrandom?/wasm_js",
+  "concision-init/wasm",
+  "concision-params/wasm",
+  "concision-traits/wasm",
+  "concision-utils?/wasm",
 ]
 # ************* [FF:Dependencies] *************
 alloc = [
-    "concision-init?/alloc",
-    "concision-utils?/alloc",
-    "ndtensor/alloc",
-    "num/alloc",
-    "serde?/alloc",
-    "serde_json?/alloc",
-    "scsys/alloc",
-]
-
-anyhow = [
-    "dep:anyhow",
-    "ndtensor/anyhow",
-    "scsys/anyhow",
+  "concision-init/alloc",
+  "concision-params/alloc",
+  "concision-traits/alloc",
+  "concision-utils?/alloc",
+  "num/alloc",
+  "serde?/alloc",
+  "serde_json?/alloc",
+  "variants/alloc",
 ]
 
 approx = [
-    "dep:approx",
-    "concision-init?/approx",
-    "concision-utils?/approx",
-    "ndarray/approx",
-    "ndtensor/approx",
+  "dep:approx",
+  "concision-init/approx",
+  "concision-params/approx",
+  "concision-utils?/approx",
+  "ndarray/approx",
 ]
 
 blas = [
-    "concision-init?/blas",
-    "concision-utils?/blas",
-    "ndarray/blas",
-    "ndtensor/blas",
+  "concision-init/blas",
+  "concision-params/blas",
+  "concision-utils?/blas",
+  "ndarray/blas",
 ]
 
 complex = [
-    "dep:num-complex",
-    "concision-init?/complex",
-    "concision-utils?/complex",
-    "ndtensor/complex",
+  "dep:num-complex",
+  "concision-init/complex",
+  "concision-params/complex",
+  "concision-utils?/complex",
 ]
 
 rand = [
-    "dep:rand",
-    "dep:rand_distr",
-    "concision-init?/rand",
-    "concision-utils?/rand",
-    "ndtensor/rand",
-    "num/rand",
-    "num-complex?/rand",
-    "rng",
-    "scsys/rand",
+  "dep:rand",
+  "dep:rand_distr",
+  "concision-init/rand",
+  "concision-params/rand",
+  "concision-traits/rand",
+  "concision-utils?/rand",
+  "num/rand",
+  "num-complex?/rand",
+  "rng",
 ]
 
 rayon = [
-    "dep:rayon",
-    "concision-utils?/rayon",
-    "ndarray/rayon",
-    "ndtensor/rayon",
+  "dep:rayon",
+  "concision-params/rayon",
+  "concision-utils?/rayon",
+  "ndarray/rayon",
 ]
 
 rng = [
-    "dep:getrandom",
-    "concision-init?/rng",
-    "concision-utils?/rng",
-    "ndtensor/rng",
-    "rand?/small_rng",
-    "rand?/thread_rng",
-    "scsys/rng",
+  "dep:getrandom",
+  "concision-init/rng",
+  "concision-params/rng",
+  "concision-traits/rng",
+  "concision-utils?/rng",
+  "rand?/small_rng",
+  "rand?/thread_rng",
 ]
 
 rustfft = ["dep:rustfft"]
 
 serde = [
-    "concision-init?/serde",
-    "concision-utils?/serde",
-    "dep:serde",
-    "dep:serde_derive",
-    "ndarray/serde",
-    "ndtensor/serde",
-    "num/serde",
-    "num-complex?/serde",
-    "rand?/serde",
-    "rand_distr?/serde",
-    "scsys/serde",
+  "dep:serde",
+  "dep:serde_derive",
+  "concision-init/serde",
+  "concision-params/serde",
+  "concision-utils?/serde",
+  "ndarray/serde",
+  "num/serde",
+  "num-complex?/serde",
+  "rand?/serde",
+  "rand_distr?/serde",
 ]
 
 serde_json = ["dep:serde_json"]
 
 tracing = [
-    "concision-init?/tracing",
-    "concision-utils?/tracing",
-    "dep:tracing",
-    "ndtensor/tracing",
-    "scsys/tracing",
+  "concision-init/tracing",
+  "concision-utils?/tracing",
+  "dep:tracing",
 ]
 
 # ************* [Unit Tests] *************
diff --git a/core/src/activate/impls/impl_binary.rs b/core/src/activate/impls/impl_binary.rs
index 9602f4e4..16421cd8 100644
--- a/core/src/activate/impls/impl_binary.rs
+++ b/core/src/activate/impls/impl_binary.rs
@@ -33,7 +33,7 @@ impl_heavyside!(
     f32, f64, i8, i16, i32, i64, i128, isize, u8, u16, u32, u64, u128, usize,
 );
 
-impl<A, B, S, D> Heavyside for ArrayBase<S, D>
+impl<A, B, S, D> Heavyside for ArrayBase<S, D, A>
 where
     A: Clone + Heavyside<Output = B>,
     D: Dimension,
@@ -50,7 +50,7 @@ where
     }
 }
 
-impl<A, B, S, D> Heavyside for &ArrayBase<S, D>
+impl<A, B, S, D> Heavyside for &ArrayBase<S, D, A>
 where
     A: Clone + Heavyside<Output = B>,
     D: Dimension,
diff --git a/core/src/activate/impls/impl_nonlinear.rs b/core/src/activate/impls/impl_nonlinear.rs
index f10d4805..a6e793c7 100644
--- a/core/src/activate/impls/impl_nonlinear.rs
+++ b/core/src/activate/impls/impl_nonlinear.rs
@@ -7,7 +7,7 @@ use crate::activate::{ReLU, Sigmoid, Softmax, Tanh, utils::sigmoid_derivative};
 use ndarray::{Array, ArrayBase, Data, Dimension, ScalarOperand};
 use num_traits::{Float, One, Zero};
 
-impl<A, S, D> ReLU for ArrayBase<S, D>
+impl<A, S, D> ReLU for ArrayBase<S, D, A>
 where
     A: Copy + PartialOrd + Zero + One,
     S: Data<Elem = A>,
@@ -24,7 +24,7 @@ where
     }
 }
 
-impl<A, S, D> Sigmoid for ArrayBase<S, D>
+impl<A, S, D> Sigmoid for ArrayBase<S, D, A>
 where
     A: ScalarOperand + Float,
     S: Data<Elem = A>,
@@ -44,7 +44,7 @@ where
     }
 }
 
-impl<A, S, D> Softmax for ArrayBase<S, D>
+impl<A, S, D> Softmax for ArrayBase<S, D, A>
 where
     A: ScalarOperand + Float,
     S: Data<Elem = A>,
@@ -67,7 +67,7 @@ where
     }
 }
 
-impl<A, S, D> Tanh for ArrayBase<S, D>
+impl<A, S, D> Tanh for ArrayBase<S, D, A>
 where
     A: ScalarOperand + Float,
     S: Data<Elem = A>,
diff --git a/core/src/activate/utils/non_linear.rs b/core/src/activate/utils/non_linear.rs
index f9374282..3af4249c 100644
--- a/core/src/activate/utils/non_linear.rs
+++ b/core/src/activate/utils/non_linear.rs
@@ -51,7 +51,7 @@ where
 /// ```math
 /// f(x_i) = \frac{e^{x_i}}{\sum_j e^{x_j}}
 /// ```
-pub fn softmax<A, S, D>(args: &ArrayBase<S, D>) -> Array<A, D>
+pub fn softmax<A, S, D>(args: &ArrayBase<S, D, A>) -> Array<A, D>
 where
     A: Float + ScalarOperand,
     D: Dimension,
@@ -65,7 +65,7 @@ where
 /// ```math
 /// f(x_i) = \frac{e^{x_i}}{\sum_j e^{x_j}}
 /// ```
-pub fn softmax_axis<A, S, D>(args: &ArrayBase<S, D>, axis: usize) -> Array<A, D>
+pub fn softmax_axis<A, S, D>(args: &ArrayBase<S, D, A>, axis: usize) -> Array<A, D>
 where
     A: Float + ScalarOperand,
     D: RemoveAxis,
diff --git a/core/src/error.rs b/core/src/error.rs
index e8d411e3..bd0fdde9 100644
--- a/core/src/error.rs
+++ b/core/src/error.rs
@@ -23,18 +23,14 @@ pub enum Error {
     #[error(transparent)]
     PadError(#[from] crate::ops::pad::error::PadError),
     #[error(transparent)]
-    ParamError(#[from] crate::params::error::ParamsError),
+    TraitError(#[from] concision_traits::Error),
     #[error(transparent)]
-    #[cfg(feature = "cnc_init")]
-    InitError(#[from] concision_init::error::InitError),
+    ParamError(#[from] concision_params::ParamsError),
     #[error(transparent)]
-    TensorError(#[from] ndtensor::error::TensorError),
+    InitError(#[from] concision_init::InitError),
     #[error(transparent)]
-    #[cfg(feature = "cnc_utils")]
+    #[cfg(feature = "concision_utils")]
     UtilityError(#[from] concision_utils::error::UtilityError),
-    #[cfg(feature = "anyhow")]
-    #[error(transparent)]
-    AnyError(#[from] anyhow::Error),
     #[cfg(feature = "alloc")]
     #[error(transparent)]
     BoxError(#[from] Box<dyn core::error::Error + Send + Sync>),
@@ -76,6 +72,7 @@ impl Error {
         Self::Unknown(error.to_string())
     }
 }
+
 #[cfg(feature = "alloc")]
 impl From<String> for Error {
     fn from(value: String) -> Self {
diff --git a/core/src/lib.rs b/core/src/lib.rs
index c8e37a85..a3e01201 100644
--- a/core/src/lib.rs
+++ b/core/src/lib.rs
@@ -40,7 +40,7 @@
 #![crate_type = "lib"]
 
 #[cfg(not(all(feature = "std", feature = "alloc")))]
-compile_error! {
+compiler_error! {
     "At least one of the 'std' or 'alloc' features must be enabled."
 }
 
@@ -54,27 +54,33 @@ pub use rand;
 #[doc(no_inline)]
 pub use rand_distr;
 
+#[doc(inline)]
+pub use concision_traits as traits;
+
 /// this module establishes generic random initialization routines for models, params, and
 /// tensors.
 #[doc(inline)]
-#[cfg(feature = "cnc_init")]
 pub use concision_init as init;
+/// The [`params`] module works to provide a generic structure for handling weights and biases
+#[doc(inline)]
+pub use concision_params as params;
 /// this module implements various utilities useful for developing machine learning models
 #[doc(inline)]
-#[cfg(feature = "cnc_utils")]
+#[cfg(feature = "concision_utils")]
 pub use concision_utils as utils;
-/// An n-dimensional tensor
-pub use ndtensor as tensor;
 
-#[cfg(feature = "cnc_init")]
-pub use self::init::prelude::*;
-#[cfg(feature = "cnc_utils")]
+#[cfg(feature = "concision_utils")]
 pub use self::utils::prelude::*;
 
 #[doc(inline)]
 pub use self::{
-    activate::prelude::*, error::*, loss::prelude::*, ops::prelude::*, params::prelude::*,
-    tensor::prelude::*, traits::*,
+    activate::prelude::*,
+    error::*,
+    init::{Init, InitInplace, Initialize},
+    loss::prelude::*,
+    ops::prelude::*,
+    params::prelude::*,
+    traits::prelude::*,
 };
 
 #[macro_use]
@@ -88,9 +94,6 @@ pub mod activate;
 pub mod error;
 /// this module focuses on the loss functions used in training neural networks.
 pub mod loss;
-/// this module provides the [`ParamsBase`] type for the library, which is used to define the
-/// parameters of a neural network.
-pub mod params;
 
 pub mod ops {
     //! This module provides the core operations for tensors, including filling, padding,
@@ -98,74 +101,24 @@ pub mod ops {
     #[doc(inline)]
     pub use self::prelude::*;
 
-    pub mod fill;
     pub mod mask;
-    pub mod norm;
     pub mod pad;
-    pub mod reshape;
 
     pub(crate) mod prelude {
-        #[doc(inline)]
-        pub use super::fill::*;
         #[doc(inline)]
         pub use super::mask::*;
         #[doc(inline)]
-        pub use super::norm::*;
-        #[doc(inline)]
         pub use super::pad::*;
-        #[doc(inline)]
-        pub use super::reshape::*;
-    }
-}
-
-pub mod traits {
-    //! This module provides the core traits for the library, such as  [`Backward`] and
-    //! [`Forward`]
-    #[doc(inline)]
-    pub use self::prelude::*;
-
-    mod apply;
-    mod clip;
-    mod codex;
-    mod convert;
-    mod gradient;
-    mod like;
-    mod propagation;
-    mod shape;
-    mod store;
-    mod wnb;
-
-    mod prelude {
-        #[doc(inline)]
-        pub use super::apply::*;
-        #[doc(inline)]
-        pub use super::clip::*;
-        #[doc(inline)]
-        pub use super::codex::*;
-        #[doc(inline)]
-        pub use super::convert::*;
-        #[doc(inline)]
-        pub use super::gradient::*;
-        #[doc(inline)]
-        pub use super::like::*;
-        #[doc(inline)]
-        pub use super::propagation::*;
-        #[doc(inline)]
-        pub use super::shape::*;
-        #[doc(inline)]
-        pub use super::store::*;
-        #[doc(inline)]
-        pub use super::wnb::*;
     }
 }
 
 #[doc(hidden)]
 pub mod prelude {
-    #[cfg(feature = "cnc_init")]
     pub use concision_init::prelude::*;
-    #[cfg(feature = "cnc_utils")]
+    pub use concision_params::prelude::*;
+    pub use concision_traits::prelude::*;
+    #[cfg(feature = "concision_utils")]
     pub use concision_utils::prelude::*;
-    pub use ndtensor::prelude::*;
 
     #[doc(no_inline)]
     pub use crate::activate::prelude::*;
@@ -173,8 +126,4 @@ pub mod prelude {
     pub use crate::loss::prelude::*;
     #[doc(no_inline)]
     pub use crate::ops::prelude::*;
-    #[doc(no_inline)]
-    pub use crate::params::prelude::*;
-    #[doc(no_inline)]
-    pub use crate::traits::*;
 }
diff --git a/core/src/loss/traits/entropy.rs b/core/src/loss/traits/entropy.rs
index 72959006..0d40da4f 100644
--- a/core/src/loss/traits/entropy.rs
+++ b/core/src/loss/traits/entropy.rs
@@ -17,7 +17,7 @@ pub trait CrossEntropy {
 use ndarray::{ArrayBase, Data, Dimension, ScalarOperand};
 use num_traits::{Float, FromPrimitive};
 
-impl<A, S, D> CrossEntropy for ArrayBase<S, D>
+impl<A, S, D> CrossEntropy for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
diff --git a/core/src/loss/traits/standard.rs b/core/src/loss/traits/standard.rs
index ca970006..0b922fe7 100644
--- a/core/src/loss/traits/standard.rs
+++ b/core/src/loss/traits/standard.rs
@@ -33,7 +33,7 @@ pub trait MeanSquaredError {
 use ndarray::{ArrayBase, Data, Dimension, ScalarOperand};
 use num_traits::{Float, FromPrimitive};
 
-impl<A, S, D> MeanAbsoluteError for ArrayBase<S, D>
+impl<A, S, D> MeanAbsoluteError for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
@@ -46,7 +46,7 @@ where
     }
 }
 
-impl<A, S, D> MeanSquaredError for ArrayBase<S, D>
+impl<A, S, D> MeanSquaredError for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
diff --git a/core/src/ops/mask/dropout.rs b/core/src/ops/mask/dropout.rs
index 9dafd661..62d3417a 100644
--- a/core/src/ops/mask/dropout.rs
+++ b/core/src/ops/mask/dropout.rs
@@ -6,7 +6,7 @@ pub trait DropOut {
 }
 
 #[cfg(feature = "init")]
-impl<A, S, D> DropOut for ndarray::ArrayBase<S, D>
+impl<A, S, D> DropOut for ndarray::ArrayBase<S, D, A>
 where
     A: num_traits::Num + ndarray::ScalarOperand,
     D: ndarray::Dimension,
@@ -15,7 +15,7 @@ where
     type Output = ndarray::Array<A, D>;
 
     fn dropout(&self, p: f64) -> Self::Output {
-        pub use crate::init::Initialize;
+        pub use concision_init::Initialize;
         use ndarray::Array;
         let dim = self.dim();
         // Create a mask of the same shape as the input array
diff --git a/core/src/ops/norm.rs b/core/src/ops/norm.rs
deleted file mode 100644
index 46ed66ae..00000000
--- a/core/src/ops/norm.rs
+++ /dev/null
@@ -1,14 +0,0 @@
-/*
-    appellation: norm <module>
-    authors: @FL03
-*/
-//! this module implements various normalization operations for tensors
-#[doc(inline)]
-pub use self::prelude::*;
-
-mod l_norm;
-
-mod prelude {
-    #[doc(inline)]
-    pub use super::l_norm::*;
-}
diff --git a/core/src/ops/pad.rs b/core/src/ops/pad.rs
index b6be6e0e..6564b9ab 100644
--- a/core/src/ops/pad.rs
+++ b/core/src/ops/pad.rs
@@ -32,7 +32,7 @@ pub struct Padding<T> {
 use ndarray::{Array, ArrayBase, DataOwned, Dimension};
 use num::traits::{FromPrimitive, Num};
 
-impl<A, S, D> Pad<A> for ArrayBase<S, D>
+impl<A, S, D> Pad<A> for ArrayBase<S, D, A>
 where
     A: Copy + FromPrimitive + Num,
     D: Dimension,
diff --git a/core/src/ops/pad/mode.rs b/core/src/ops/pad/mode.rs
index 8d8e43a8..7dd96abd 100644
--- a/core/src/ops/pad/mode.rs
+++ b/core/src/ops/pad/mode.rs
@@ -14,7 +14,7 @@ use num::Zero;
     Ord,
     PartialEq,
     PartialOrd,
-    scsys_derive::VariantConstructors,
+    variants::VariantConstructors,
     strum::AsRefStr,
     strum::Display,
     strum::EnumCount,
diff --git a/core/src/ops/pad/utils.rs b/core/src/ops/pad/utils.rs
index e2f04955..75ad6234 100644
--- a/core/src/ops/pad/utils.rs
+++ b/core/src/ops/pad/utils.rs
@@ -19,7 +19,7 @@ fn reader(nb_dim: usize, pad: &[[usize; 2]]) -> Result<Vec<[usize; 2]>, PadError
 }
 
 pub fn pad<A, S, D>(
-    data: &ArrayBase<S, D>,
+    data: &ArrayBase<S, D, A>,
     pad: &[[usize; 2]],
     mode: PadMode<A>,
 ) -> Result<Array<A, D>, PadError>
@@ -40,7 +40,7 @@ where
 }
 
 pub fn pad_to<A, S, D>(
-    data: &ArrayBase<S, D>,
+    data: &ArrayBase<S, D, A>,
     pad: &[[usize; 2]],
     mode: PadMode<A>,
     output: &mut Array<A, D>,
diff --git a/core/tests/params.rs b/core/tests/params.rs
index 52b6b516..fc591f97 100644
--- a/core/tests/params.rs
+++ b/core/tests/params.rs
@@ -2,39 +2,11 @@
     Appellation: params <test>
     Contrib: @FL03
 */
-extern crate concision_core as cnc;
-use cnc::params::Params;
+use concision_params::Params;
 
 use approx::assert_abs_diff_eq;
 use ndarray::prelude::*;
 
-#[test]
-fn test_params_ones() {
-    // weights retain the given shape (d_in, d_out)
-    // bias retains the shape (d_out,)
-    let ones = Params::<f64>::ones((3, 4));
-    assert_eq!(ones.dim(), (3, 4));
-    assert_eq!(ones.bias().dim(), 4);
-    assert!(
-        ones.iter()
-            .all(|(w, b)| w.iter().all(|&wi| wi == 1.0) && b == &1.0)
-    );
-}
-
-#[test]
-fn test_params_zeros() {
-    // weights retain the given shape (d_in, d_out)
-    // bias retains the shape (d_out,)
-    let zeros = Params::<f64>::zeros((3, 4));
-    assert_eq!(zeros.dim(), (3, 4));
-    assert_eq!(zeros.bias().dim(), 4);
-    assert!(
-        zeros
-            .iter()
-            .all(|(w, b)| w.iter().all(|&wi| wi == 0.0) && b == &0.0)
-    );
-}
-
 #[test]
 fn test_params_forward() {
     let params = Params::<f64>::ones((3, 4));
@@ -46,22 +18,3 @@ fn test_params_forward() {
     // where W = ones(3, 4) and b = ones(4)
     assert_abs_diff_eq!(output, array![7.0, 7.0, 7.0, 7.0], epsilon = 1e-3);
 }
-
-#[test]
-#[cfg(feature = "init")]
-fn test_params_init() {
-    use cnc::init::Initialize;
-
-    let lecun = Params::<f64>::lecun_normal((3, 4));
-    assert_eq!(lecun.dim(), (3, 4));
-
-    let glorot_norm = Params::<f64>::glorot_normal((3, 4));
-    assert_eq!(glorot_norm.dim(), (3, 4));
-    assert_ne!(lecun, glorot_norm);
-    let glorot_uniform = Params::<f64>::glorot_uniform((3, 4)).expect("glorot_uniform failed");
-    assert_eq!(glorot_uniform.dim(), (3, 4));
-    assert_ne!(lecun, glorot_uniform);
-    assert_ne!(glorot_norm, glorot_uniform);
-    let truncnorm = Params::<f64>::truncnorm((3, 4), 0.0, 1.0).expect("truncnorm failed");
-    assert_eq!(truncnorm.dim(), (3, 4));
-}
diff --git a/data/Cargo.toml b/data/Cargo.toml
index dfbdc3d3..6fb68f9c 100644
--- a/data/Cargo.toml
+++ b/data/Cargo.toml
@@ -2,7 +2,6 @@
 build = "build.rs"
 description = "this crate provides additional tools for working with datasets"
 name = "concision-data"
-
 authors.workspace = true
 categories.workspace = true
 edition.workspace = true
@@ -14,33 +13,26 @@ repository.workspace = true
 rust-version.workspace = true
 version.workspace = true
 
-[package.metadata.docs.rs]
-all-features = false
-doc-scrape-examples = true
-features = ["full"]
-rustc-args = ["--cfg", "docsrs"]
-version = "v{{version}}"
-
-[package.metadata.release]
-no-dev-version = true
-tag-name = "{{version}}"
-
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
+crate-type = ["cdylib","rlib"]
 bench = false
 doc = true
 doctest = true
 test = true
 
+# ************* [Unit Tests] *************
+[[test]]
+name = "default"
+
+[[test]]
+name = "loader"
+required-features = ["loader"]
+
 [dependencies]
 concision-core = { workspace = true }
 # custom
-scsys = { workspace = true }
+variants = { workspace = true }
 # error handling
-anyhow = { optional = true, workspace = true }
 thiserror = { workspace = true }
 # mathematics
 approx = { optional = true, workspace = true }
@@ -65,7 +57,6 @@ default = [
 
 full = [
     "default",
-    "anyhow",
     "approx",
     "complex",
     "json",
@@ -91,33 +82,26 @@ std = [
     "ndarray/std",
     "num/std",
     "num-complex?/std",
-    "scsys/std",
     "serde?/std",
     "serde_json?/std",
     "tracing?/std",
+    "variants/std",
 ]
 
 wasi = [
     "concision-core/wasi",
-    "scsys/wasi",
 ]
 
 wasm = [
     "concision-core/wasm",
-    "scsys/wasm",
 ]
 
 # ************* [FF:Dependencies] *************
 alloc = [
     "concision-core/alloc",
     "num/alloc",
-    "serde?/alloc"
-]
-
-anyhow = [
-    "dep:anyhow", 
-    "concision-core/anyhow",
-    "scsys/anyhow",
+    "serde?/alloc",
+    "variants/alloc",
 ]
 
 approx = [
@@ -142,7 +126,6 @@ json = [
     "serde_json",
     "concision-core/json",
     "reqwest?/json",
-    "scsys/json",
 ]
 
 rayon = [
@@ -153,12 +136,10 @@ rayon = [
 rand = [
     "concision-core/rand", 
     "rng",
-    "scsys/rand",
 ]
 
 rng = [
     "concision-core/rng",
-    "scsys/rng",
 ]
 
 reqwest = ["dep:reqwest"]
@@ -169,7 +150,6 @@ serde = [
     "ndarray/serde",
     "num/serde",
     "num-complex?/serde",
-    "scsys/serde",
 ]
 
 serde_json = ["dep:serde_json"]
@@ -177,13 +157,16 @@ serde_json = ["dep:serde_json"]
 tracing = [
     "concision-core/tracing",
     "dep:tracing",
-    "scsys/tracing",
 ]
 
-# ************* [Unit Tests] *************
-[[test]]
-name = "default"
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+doc-scrape-examples = true
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
 
-[[test]]
-name = "loader"
-required-features = ["loader"]
\ No newline at end of file
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
diff --git a/ext/Cargo.toml b/ext/Cargo.toml
index 4fa73751..279468b0 100644
--- a/ext/Cargo.toml
+++ b/ext/Cargo.toml
@@ -25,11 +25,8 @@ no-dev-version = true
 tag-name = "{{version}}"
 
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
 bench = false
+crate-type = ["cdylib", "rlib"]
 doc = true
 doctest = true
 test = true
@@ -38,13 +35,11 @@ test = true
 # local
 concision = { features = ["neural"], workspace = true }
 # custom
-scsys = { workspace = true }
+variants = { workspace = true }
 # concurrency & parallelism
 rayon = { optional = true, workspace = true }
 # data-structures
 ndarray = { workspace = true }
-# error handling
-anyhow = { optional = true, workspace = true }
 # mathematics
 approx = { optional = true, workspace = true }
 num = { workspace = true }
@@ -60,138 +55,95 @@ tracing = { optional = true, workspace = true }
 
 [dev-dependencies]
 anyhow = { features = ["std"], workspace = true }
-lazy_static ={ workspace = true }
+lazy_static = { workspace = true }
 tracing-subscriber = { features = ["std"], workspace = true }
 
 [features]
-default = [
-    "attention",
-    "std",
-]
+default = ["attention", "std"]
 
 full = [
-    "default",
-    "anyhow",
-    "complex",
-    "rand",
-    "json",
-    "serde",
-    "tracing"
+  "complex", 
+  "default", 
+  "json", 
+  "rand", 
+  "serde", 
+  "tracing"
 ]
 
-nightly = [
-    "concision/nightly",
-]
+nightly = ["concision/nightly"]
 
 # ************* [FF:Features] *************
 attention = []
 
 signal = [
-    "complex",
-    "rustfft"
+  "complex", "rustfft"
 ]
 
 json = [
-    "alloc",
-    "serde",
-    "serde_json",
+  "alloc", "serde", "serde_json"
 ]
 
 init = [
-    "concision/init", 
-    "rand"
+  "concision/init", "rand"
 ]
 # ************* [FF:Environments] *************
 std = [
-    "alloc",
-    "anyhow?/std",
-    "approx?/std",
-    "concision/std",
-    "ndarray/std",
-    "num/std",
-    "num-complex?/std",
-    "num-traits/std",
-    "scsys/std",
-    "serde?/std",
-    "serde_json?/std",
-    "tracing?/std",
+  "alloc", 
+  "approx?/std", 
+  "concision/std", 
+  "ndarray/std", 
+  "num-complex?/std", 
+  "num-traits/std", 
+  "num/std", 
+  "serde?/std", 
+  "serde_json?/std", 
+  "tracing?/std", 
+  "variants/std"
 ]
 
-wasi = [
-    "concision/wasi",
-    "scsys/wasi",
-]
+wasi = ["concision/wasi"]
 
 wasm = [
-    "concision/wasm",
-    "scsys/wasm",
-    "rayon?/web_spin_lock",
+  "concision/wasm", 
+  "rayon?/web_spin_lock"
 ]
 # ************* [FF:Dependencies] *************
 alloc = [
-    "concision/alloc",
-    "num/alloc",
-    "scsys/alloc",
-    "serde?/alloc",
-    "serde_json?/alloc",
-]
-
-anyhow = [
-    "dep:anyhow",
-    "concision/anyhow",
-    "scsys/anyhow",
+  "concision/alloc", 
+  "num/alloc", 
+  "serde?/alloc", 
+  "serde_json?/alloc", 
+  "variants/alloc"
 ]
 
-approx = [
-    "dep:approx",
-    "concision/approx",
-    "ndarray/approx",
-]
+approx = ["concision/approx", "dep:approx", "ndarray/approx"]
 
-blas = [
-    "concision/blas",
-    "ndarray/blas",
-]
+blas = ["concision/blas", "ndarray/blas"]
 
 complex = ["dep:num-complex"]
 
-rand = [
-    "concision/rand",
-    "num/rand",
-    "num-complex?/rand",
-]
+rand = ["concision/rand", "num-complex?/rand", "num/rand"]
 
-rayon = [
-    "concision/rayon",
-    "ndarray/rayon",
-]
+rayon = ["concision/rayon", "ndarray/rayon"]
 
-rng = [
-    "concision/rng",
-    "scsys/rng",
-]
+rng = ["concision/rng"]
 
 rustfft = ["dep:rustfft"]
 
 serde = [
-    "dep:serde",
-    "dep:serde_derive",
-    "concision/serde",
-    "ndarray/serde",
-    "num/serde",
-    "num-complex?/serde",
-    "scsys/serde",
+  "concision/serde", 
+  "dep:serde",
+   "dep:serde_derive", 
+   "ndarray/serde", 
+   "num-complex?/serde", 
+   "num/serde"
 ]
 
 serde_json = ["dep:serde_json"]
 
-tracing = [
-    "dep:tracing",
-    "concision/tracing",
-    "scsys/tracing",
-]
+tracing = ["concision/tracing", "dep:tracing"]
 
 # ************* [Unit Tests] *************
 [[test]]
 name = "attention"
-required-features = ["approx", "attention", "default", "rand"]
\ No newline at end of file
+required-features = ["approx", "attention", "default", "rand"]
diff --git a/ext/src/attention/qkv.rs b/ext/src/attention/qkv.rs
index f25425e1..0d6a502b 100644
--- a/ext/src/attention/qkv.rs
+++ b/ext/src/attention/qkv.rs
@@ -129,11 +129,11 @@ where
 {
     type Output = Z;
 
-    fn forward(&self, input: &X) -> cnc::Result<Self::Output> {
+    fn forward(&self, input: &X) -> Option<Self::Output> {
         let query = input.dot(&self.query);
         let key = input.dot(&self.key);
         let value = input.dot(&self.value);
         let output = query + key + value;
-        Ok(output)
+        Some(output)
     }
 }
diff --git a/init/Cargo.toml b/init/Cargo.toml
index 896eac0d..7075650f 100644
--- a/init/Cargo.toml
+++ b/init/Cargo.toml
@@ -25,11 +25,8 @@ no-dev-version = true
 tag-name = "{{version}}"
 
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
 bench = false
+crate-type = ["cdylib", "rlib"]
 doc = true
 doctest = true
 test = true
@@ -40,7 +37,6 @@ serde = { features = ["derive"], optional = true, workspace = true }
 serde_derive = { optional = true, workspace = true }
 serde_json = { optional = true, workspace = true }
 # error-handling
-anyhow = { optional = true, workspace = true }
 thiserror = { workspace = true }
 # logging
 tracing = { optional = true, workspace = true }
@@ -63,80 +59,51 @@ rand_distr = { optional = true, workspace = true }
 lazy_static = { workspace = true }
 
 [features]
-default = [
-    "rand",
-    "std",
-]
+default = ["rand", "std"]
 
-full = [
-    "approx",
-    "complex",
-    "default",
-    "serde",
-    "tracing",
-]
+full = ["approx", "complex", "default", "serde", "tracing"]
 
 nightly = []
 
-
 # ************* [FF:Dependencies] *************
 std = [
-    "alloc",
-    "anyhow?/std",
-    "ndarray/std",
-    "num/std",
-    "num-complex?/std",
-    "num-traits/std",
-    "rand/std",
-    "rand/std_rng",
-    "serde/std",
-    "strum/std",
-    "thiserror/std",
-    "tracing?/std",
+  "alloc", 
+  "ndarray/std", 
+  "num-complex?/std", 
+  "num-traits/std", 
+  "num/std", 
+  "rand/std", 
+  "rand/std_rng", 
+  "serde/std", 
+  "strum/std", 
+  "thiserror/std", 
+  "tracing?/std"
 ]
 
 wasi = []
 
-wasm = [
-    "getrandom?/wasm_js",
-]
+wasm = ["getrandom?/wasm_js"]
 # ************* [FF:Dependencies] *************
-alloc = [
-    "num/alloc",
-    "serde?/alloc",
-]
+alloc = ["num/alloc", "serde?/alloc"]
 
-approx = [
-    "dep:approx",
-    "ndarray/approx",
-]
+approx = ["dep:approx", "ndarray/approx"]
 
 blas = ["ndarray/blas"]
 
 complex = ["dep:num-complex"]
 
-rand = [
-    "dep:rand",
-    "dep:rand_distr",
-    "num/rand",
-    "num-complex?/rand",
-    "rng",
-]
+rand = ["dep:rand", "dep:rand_distr", "num-complex?/rand", "num/rand", "rng"]
 
-rng = [
-    "dep:getrandom",
-    "rand?/small_rng",
-    "rand?/thread_rng",
-]
+rng = ["dep:getrandom", "rand?/small_rng", "rand?/thread_rng"]
 
 serde = [
-    "dep:serde",
-    "dep:serde_derive",
-    "ndarray/serde",
-    "num/serde",
-    "num-complex?/serde",
-    "rand?/serde",
-    "rand_distr?/serde",
+  "dep:serde", 
+  "dep:serde_derive", 
+  "ndarray/serde", 
+  "num-complex?/serde", 
+  "num/serde", 
+  "rand?/serde", 
+  "rand_distr?/serde"
 ]
 
 tracing = ["dep:tracing"]
diff --git a/models/kan/Cargo.toml b/models/kan/Cargo.toml
index 9aae7f8e..9793ea29 100644
--- a/models/kan/Cargo.toml
+++ b/models/kan/Cargo.toml
@@ -25,11 +25,8 @@ no-dev-version = true
 tag-name = "{{version}}"
 
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
 bench = false
+crate-type = ["cdylib", "rlib"]
 doc = true
 doctest = true
 test = true
@@ -38,7 +35,7 @@ test = true
 # sdk
 concision = { features = ["neural"], workspace = true }
 # error
-anyhow = { optional = true, workspace = true }
+anyhow = { workspace = true }
 # mathematics
 approx = { optional = true, workspace = true }
 ndarray = { workspace = true }
@@ -47,63 +44,26 @@ num-traits = { workspace = true }
 tracing = { optional = true, workspace = true }
 
 [features]
-default = [
-    "std",
-]
+default = ["std"]
 
-full = [
-    "default",
-    "rand",
-    "serde",
-    "tracing"
-]
+full = ["default", "rand", "serde", "tracing"]
 
 # ************* [FF:Environments] *************
-std = [
-    "concision/std",
-    "ndarray/std",
-    "num-traits/std",
-    "tracing/std",
-]
+std = ["concision/std", "ndarray/std", "num-traits/std", "tracing/std"]
 
-wasi = [
-    "concision/wasi",
-]
+wasi = ["concision/wasi"]
 
-wasm = [
-    "concision/wasm",
-]
+wasm = ["concision/wasm"]
 
 # ************* [FF:Dependencies] *************
-anyhow = [
-    "dep:anyhow",
-    "concision/anyhow",
-]
-approx = [
-    "dep:approx",
-    "concision/approx",
-    "ndarray/approx",
-]
-
-blas = [
-    "concision/blas",
-    "ndarray/blas"
-]
-
-rand = [
-    "concision/rand",
-]
-
-rayon = [
-    "concision/rayon",
-    "ndarray/rayon"
-]
-
-serde = [
-    "concision/serde",
-]
-
-tracing = [
-    "dep:tracing",
-    "concision/tracing",
-]
+approx = ["concision/approx", "dep:approx", "ndarray/approx"]
+
+blas = ["concision/blas", "ndarray/blas"]
+
+rand = ["concision/rand"]
+
+rayon = ["concision/rayon", "ndarray/rayon"]
+
+serde = ["concision/serde"]
+
+tracing = ["concision/tracing", "dep:tracing"]
diff --git a/models/models/Cargo.toml b/models/models/Cargo.toml
index a40f62c6..71eb27ea 100644
--- a/models/models/Cargo.toml
+++ b/models/models/Cargo.toml
@@ -14,27 +14,23 @@ repository.workspace = true
 rust-version.workspace = true
 version.workspace = true
 
-[package.metadata.docs.rs]
-all-features = false
-doc-scrape-examples = true
-features = ["full"]
-rustc-args = ["--cfg", "docsrs"]
-version = "v{{version}}"
-
-[package.metadata.release]
-no-dev-version = true
-tag-name = "{{version}}"
-
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
+crate-type = ["cdylib",  "rlib"]
 bench = false
 doc = true
 doctest = true
 test = true
 
+# ************* [Examples] *************
+[[example]]
+name = "simple"
+required-features = ["approx", "rand", "tracing"]
+
+# ************* [Unit Tests] *************
+[[test]]
+name = "simple"
+required-features = ["approx", "rand"]
+
 [dependencies]
 concision-kan = { optional = true, workspace = true }
 concision-s4 = { optional = true, workspace = true }
@@ -43,9 +39,7 @@ concision-transformer = { optional = true, workspace = true }
 concision = { features = ["neural"], workspace = true }
 concision-ext = { workspace = true }
 # custom
-scsys = { workspace = true }
-# error handling
-anyhow = { optional = true, workspace = true }
+variants = { workspace = true }
 # mathematics
 approx = { optional = true, workspace = true }
 ndarray = { workspace = true }
@@ -58,25 +52,22 @@ anyhow = { features = ["std"], workspace = true }
 lazy_static ={ workspace = true }
 tracing-subscriber = { features = ["std"], workspace = true }
 
+# ********* [Features] *********
 [features]
-default = [
-    "simple",
-    "std",
-]
+default = ["std"]
 
 full = [
-    "anyhow",
-    "default",
-    "models",
-    "rand",
-    "serde",
-    "tracing"
+  "default",
+  "models",
+  "rand",
+  "serde",
+  "tracing"
 ]
 
-# ************* [FF:Features] *************
+# ************* [FF:Flags] *************
 models = [
-    "simple",
-    "transformer"
+  "simple",
+  "transformer"
 ]
 
 simple = []
@@ -89,99 +80,79 @@ transformer = ["dep:concision-transformer"]
 
 # ************* [FF:Environments] *************
 std = [
-    "concision/std",
-    "concision-ext/std",
-    "concision-kan?/std",
-    "concision-s4?/std",
-    "concision-transformer?/std",
-    "scsys/std",
-    "ndarray/std",
-    "num-traits/std",
-    "tracing?/std",
+  "concision/std",
+  "concision-ext/std",
+  "concision-kan?/std",
+  "concision-s4?/std",
+  "concision-transformer?/std",
+  "ndarray/std",
+  "num-traits/std",
+  "tracing?/std",
 ]
 
 # ************* [FF:Dependencies] *************
-anyhow = [
-    "dep:anyhow",
-    "concision/anyhow",
-    "concision-ext/anyhow",
-    "concision-kan?/anyhow",
-    "concision-s4?/anyhow",
-    "concision-transformer?/anyhow",
-    "scsys/anyhow",
-]
-
 approx = [
-    "dep:approx",
-    "concision/approx",
-    "concision-ext/approx",
-    "concision-kan?/approx",
-    "concision-s4?/approx",
-    "concision-transformer?/approx",
-    "ndarray/approx",
+  "dep:approx",
+  "concision/approx",
+  "concision-ext/approx",
+  "concision-kan?/approx",
+  "concision-s4?/approx",
+  "concision-transformer?/approx",
+  "ndarray/approx",
 ]
 
 blas = [
-    "concision/blas",
-    "concision-ext/blas",
-    "concision-kan?/blas",
-    "concision-s4?/blas",
-    "concision-transformer?/blas",
-    "ndarray/blas",
+  "concision/blas",
+  "concision-ext/blas",
+  "concision-kan?/blas",
+  "concision-s4?/blas",
+  "concision-transformer?/blas",
+  "ndarray/blas",
 ]
 
 rand = [
-    "concision/rand",
-    "concision-ext/rand",
-    "concision-kan?/rand",
-    "concision-s4?/rand",
-    "concision-transformer?/rand",
+  "concision/rand",
+  "concision-ext/rand",
+  "concision-kan?/rand",
+  "concision-s4?/rand",
+  "concision-transformer?/rand",
 ]
 
 rayon = [
-    "concision/rayon",
-    "concision-ext/rayon",
-    "concision-kan?/rayon",
-    "concision-s4?/rayon",
-    "concision-transformer?/rayon",
-    "ndarray/rayon",
+  "concision/rayon",
+  "concision-ext/rayon",
+  "concision-kan?/rayon",
+  "concision-s4?/rayon",
+  "concision-transformer?/rayon",
+  "ndarray/rayon",
 ]
 
 serde = [
-    "concision/serde",
-    "concision-ext/rng",
-    "concision-kan?/serde",
-    "concision-s4?/serde",
-    "concision-transformer?/serde",
-    "ndarray/serde",
-    "scsys/serde",
+  "concision/serde",
+  "concision-ext/rng",
+  "concision-kan?/serde",
+  "concision-s4?/serde",
+  "concision-transformer?/serde",
+  "ndarray/serde",
 ]
 
 tracing = [
-    "dep:tracing",
-    "concision/tracing",
-    "concision-ext/tracing",
-    "concision-kan?/tracing",
-    "concision-s4?/tracing",
-    "concision-transformer?/tracing",
-    "scsys/tracing",
+  "dep:tracing",
+  "concision/tracing",
+  "concision-ext/tracing",
+  "concision-kan?/tracing",
+  "concision-s4?/tracing",
+  "concision-transformer?/tracing",
 ]
 
-# ************* [Examples] *************
-[[example]]
-name = "simple"
-required-features = [
-    "anyhow",
-    "approx",
-    "rand",
-    "tracing",
-]
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+doc-scrape-examples = true
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
 
-# ************* [FF:Dependencies] *************
-[[test]]
-name = "simple"
-required-features = [
-    "anyhow",
-    "approx",
-    "rand",
-]
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
\ No newline at end of file
diff --git a/models/models/src/simple.rs b/models/models/src/simple.rs
index 7d3fb234..ee9d005b 100644
--- a/models/models/src/simple.rs
+++ b/models/models/src/simple.rs
@@ -2,7 +2,7 @@
     Appellation: simple <module>
     Contrib: @FL03
 */
-use cnc::nn::{DeepModelParams, Model, ModelError, ModelFeatures, StandardModelConfig, Train};
+use cnc::nn::{DeepModelParams, Model, ModelFeatures, NeuralError, StandardModelConfig, Train};
 use cnc::{Forward, Norm, Params, ReLU, Sigmoid};
 
 use ndarray::prelude::*;
@@ -125,7 +125,7 @@ where
 {
     type Output = Array<A, D>;
 
-    fn forward(&self, input: &ArrayBase<S, D>) -> cnc::Result<Self::Output> {
+    fn forward(&self, input: &ArrayBase<S, D>) -> Option<Self::Output> {
         let mut output = self
             .params()
             .input()
@@ -139,7 +139,7 @@ where
             .params()
             .output()
             .forward_then(&output, |y| y.sigmoid())?;
-        Ok(y)
+        Some(y)
     }
 }
 
@@ -153,23 +153,18 @@ where
 
     #[cfg_attr(
         feature = "tracing",
-        tracing::instrument(
-            skip(self, input, target),
-            level = "trace",
-            name = "backward",
-            target = "model",
-        )
+        tracing::instrument(skip(self, input, target), level = "trace", target = "model",)
     )]
     fn train(
         &mut self,
         input: &ArrayBase<S, Ix1>,
         target: &ArrayBase<T, Ix1>,
-    ) -> Result<Self::Output, ModelError> {
-        if input.len() != self.features().input() {
-            return Err(ModelError::InvalidInputShape);
+    ) -> Result<Self::Output, NeuralError> {
+        if input.len() != self.layout().input() {
+            return Err(NeuralError::InvalidInputShape);
         }
-        if target.len() != self.features().output() {
-            return Err(ModelError::InvalidOutputShape);
+        if target.len() != self.layout().output() {
+            return Err(NeuralError::InvalidOutputShape);
         }
         // get the learning rate from the model's configuration
         let lr = self
@@ -186,15 +181,28 @@ where
         let mut activations = Vec::new();
         activations.push(input.to_owned());
 
-        let mut output = self.params().input().forward(&input)?.relu();
+        let mut output = self
+            .params()
+            .input()
+            .forward(&input)
+            .expect("Failed to complete the forward pass for the input layer")
+            .relu();
         activations.push(output.to_owned());
         // collect the activations of the hidden
         for layer in self.params().hidden() {
-            output = layer.forward(&output)?.relu();
+            output = layer
+                .forward(&output)
+                .expect("failed to complete the forward pass for the hidden layer")
+                .relu();
             activations.push(output.to_owned());
         }
 
-        output = self.params().output().forward(&output)?.sigmoid();
+        output = self
+            .params()
+            .output()
+            .forward(&output)
+            .expect("Output layer failed to forward propagate")
+            .sigmoid();
         activations.push(output.to_owned());
 
         // Calculate output layer error
@@ -208,9 +216,10 @@ where
         // Update output weights
         self.params_mut()
             .output_mut()
-            .backward(activations.last().unwrap(), &delta, lr)?;
+            .backward(activations.last().unwrap(), &delta, lr)
+            .expect("Output failed training...");
 
-        let num_hidden = self.features().layers();
+        let num_hidden = self.layout().layers();
         // Iterate through hidden layers in reverse order
         for i in (0..num_hidden).rev() {
             // Calculate error for this layer
@@ -224,7 +233,9 @@ where
             };
             // Normalize delta to prevent exploding gradients
             delta /= delta.l2_norm();
-            self.params_mut().hidden_mut()[i].backward(&activations[i + 1], &delta, lr)?;
+            self.params_mut().hidden_mut()[i]
+                .backward(&activations[i + 1], &delta, lr)
+                .expect("Hidden failed training...");
         }
         /*
             Backpropagate to the input layer
@@ -237,7 +248,8 @@ where
         delta /= delta.l2_norm(); // Normalize the delta to prevent exploding gradients
         self.params_mut()
             .input_mut()
-            .backward(&activations[1], &delta, lr)?;
+            .backward(&activations[1], &delta, lr)
+            .expect("failed to backpropagate input layer during training...");
 
         Ok(loss)
     }
@@ -265,15 +277,15 @@ where
         &mut self,
         input: &ArrayBase<S, Ix2>,
         target: &ArrayBase<T, Ix2>,
-    ) -> Result<Self::Output, ModelError> {
+    ) -> Result<Self::Output, NeuralError> {
         if input.nrows() == 0 || target.nrows() == 0 {
-            return Err(ModelError::InvalidBatchSize);
+            return Err(NeuralError::InvalidBatchSize);
         }
         if input.ncols() != self.features().input() {
-            return Err(ModelError::InvalidInputShape);
+            return Err(NeuralError::InvalidInputShape);
         }
         if target.ncols() != self.features().output() || target.nrows() != input.nrows() {
-            return Err(ModelError::InvalidOutputShape);
+            return Err(NeuralError::InvalidOutputShape);
         }
         let mut loss = A::zero();
 
diff --git a/models/s4/Cargo.toml b/models/s4/Cargo.toml
index 9bef6f98..40a42d3c 100644
--- a/models/s4/Cargo.toml
+++ b/models/s4/Cargo.toml
@@ -24,20 +24,14 @@ version = "v{{version}}"
 no-dev-version = true
 tag-name = "{{version}}"
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
 bench = false
+crate-type = ["cdylib", "rlib"]
 doc = true
 doctest = true
 test = true
 
 [dependencies]
-# sdk
 concision = { features = ["neural"], workspace = true }
-# error
-anyhow = { optional = true, workspace = true }
 # mathematics
 approx = { optional = true, workspace = true }
 ndarray = { workspace = true }
@@ -45,64 +39,30 @@ num-traits = { workspace = true }
 # logging
 tracing = { optional = true, workspace = true }
 
+[dev-dependencies]
+anyhow = { features = ["std"], workspace = true }
+
 [features]
-default = [
-    "std",
-]
+default = ["std"]
 
-full = [
-    "default",
-    "rand",
-    "serde",
-    "tracing"
-]
+full = ["default", "rand", "serde", "tracing"]
 
 # ************* [FF:Environments] *************
-std = [
-    "concision/std",
-    "ndarray/std",
-    "num-traits/std",
-    "tracing/std",
-]
+std = ["concision/std", "ndarray/std", "num-traits/std", "tracing/std"]
 
-wasi = [
-    "concision/wasi",
-]
+wasi = ["concision/wasi"]
 
-wasm = [
-    "concision/wasm",
-]
+wasm = ["concision/wasm"]
 
 # ************* [FF:Dependencies] *************
-anyhow = [
-    "dep:anyhow",
-    "concision/anyhow",
-]
-approx = [
-    "dep:approx",
-    "concision/approx",
-    "ndarray/approx",
-]
-
-blas = [
-    "concision/blas",
-    "ndarray/blas"
-]
-
-rand = [
-    "concision/rand",
-]
-
-rayon = [
-    "concision/rayon",
-    "ndarray/rayon"
-]
-
-serde = [
-    "concision/serde",
-]
-
-tracing = [
-    "dep:tracing",
-    "concision/tracing",
-]
+approx = ["concision/approx", "dep:approx", "ndarray/approx"]
+
+blas = ["concision/blas", "ndarray/blas"]
+
+rand = ["concision/rand"]
+
+rayon = ["concision/rayon", "ndarray/rayon"]
+
+serde = ["concision/serde"]
+
+tracing = ["concision/tracing", "dep:tracing"]
diff --git a/models/snn/Cargo.toml b/models/snn/Cargo.toml
new file mode 100644
index 00000000..f5d2d96e
--- /dev/null
+++ b/models/snn/Cargo.toml
@@ -0,0 +1,111 @@
+[package]
+build = "build.rs"
+description = "Synaptic Neural Networks for the Concision Machine Learning Framework"
+name = "concision-snn"
+
+authors.workspace = true
+categories.workspace = true
+edition.workspace = true
+homepage.workspace = true
+keywords.workspace = true
+license.workspace = true
+readme.workspace = true
+repository.workspace = true
+rust-version.workspace = true
+version.workspace = true
+
+[lib]
+bench = false
+crate-type = ["cdylib", "rlib"]
+doc = true
+doctest = true
+test = true
+
+# ********* [Unit Tests] *********
+[[test]]
+name = "neurons"
+required-features = ["default"]
+
+[dependencies]
+concision = { features = ["neural"], workspace = true }
+# mathematics
+approx = { optional = true, workspace = true }
+ndarray = { workspace = true }
+num-traits = { workspace = true }
+# serialization
+serde = { optional = true, workspace = true }
+serde_derive = { optional = true, workspace = true }
+serde_json = { optional = true, workspace = true }
+# logging
+tracing = { optional = true, workspace = true }
+
+[dev-dependencies]
+anyhow = { features = ["std"], workspace = true }
+
+[features]
+default = ["std"]
+
+full = [
+  "default", 
+  "json",
+  "rand", 
+  "serde", 
+  "tracing"
+]
+
+json = ["alloc", "serde", "serde_json"]
+
+# ************* [FF:Environments] *************
+std = [
+  "alloc",
+  "concision/std",
+  "ndarray/std", 
+  "num-traits/std", 
+  "serde?/std",
+  "serde_json?/std",
+  "tracing/std"
+  ]
+
+wasi = ["concision/wasi"]
+
+wasm = ["concision/wasm"]
+
+# ************* [FF:Dependencies] *************
+alloc = [
+  "concision/alloc", 
+  "serde?/alloc",
+  "serde_json?/alloc",
+]
+
+approx = [
+  "concision/approx", 
+  "dep:approx", 
+  "ndarray/approx"
+]
+
+blas = ["concision/blas", "ndarray/blas"]
+
+rand = ["concision/rand"]
+
+rayon = ["concision/rayon", "ndarray/rayon"]
+
+serde = [
+  "dep:serde", 
+  "dep:serde_derive", 
+  "concision/serde",
+]
+
+serde_json = ["dep:serde_json"]
+
+tracing = ["concision/tracing", "dep:tracing"]
+
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
+
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
diff --git a/models/snn/build.rs b/models/snn/build.rs
new file mode 100644
index 00000000..940a4ce4
--- /dev/null
+++ b/models/snn/build.rs
@@ -0,0 +1,8 @@
+/*
+    Appellation: build <build>
+    Contrib: FL03 <jo3mccain@icloud.com>
+*/
+
+fn main() {
+    println!("cargo::rustc-check-cfg=cfg(no_std)");
+}
diff --git a/models/snn/src/lib.rs b/models/snn/src/lib.rs
new file mode 100644
index 00000000..e1449010
--- /dev/null
+++ b/models/snn/src/lib.rs
@@ -0,0 +1,51 @@
+/*
+    appellation: concision-snn <library>
+    authors: @FL03
+*/
+//! Spiking neural networks (SNNs) for the [`concision`](https://crates.io/crates/concision) machine learning framework.
+//!
+//! ## References
+//!
+//! - [Deep Learning in Spiking Neural Networks](https://arxiv.org/abs/1804.08150)
+//!
+#![crate_type = "lib"]
+#![cfg_attr(not(feature = "std"), no_std)]
+#![allow(clippy::module_inception)]
+
+#[cfg(feature = "alloc")]
+extern crate alloc;
+extern crate concision as cnc;
+
+#[cfg(not(any(feature = "std", feature = "alloc")))]
+compiler_error! {
+    "Either feature \"std\" or feature \"alloc\" must be enabled."
+}
+
+#[doc(inline)]
+pub use self::{model::*, neuron::*, types::*};
+
+pub mod model;
+pub mod neuron;
+
+pub mod types {
+    //! Types for spiking neural networks
+    #[doc(inline)]
+    pub use self::prelude::*;
+
+    mod event;
+    mod result;
+
+    pub(crate) mod prelude {
+        pub use super::event::*;
+        pub use super::result::*;
+    }
+}
+
+pub mod prelude {
+    #[doc(inline)]
+    pub use crate::model::*;
+    #[doc(inline)]
+    pub use crate::neuron::*;
+    #[doc(inline)]
+    pub use crate::types::*;
+}
diff --git a/models/snn/src/model.rs b/models/snn/src/model.rs
new file mode 100644
index 00000000..4b03fc48
--- /dev/null
+++ b/models/snn/src/model.rs
@@ -0,0 +1,120 @@
+/*
+    appellation: model <module>
+    authors: @FL03
+*/
+
+use cnc::nn::{DeepModelParams, Model, ModelFeatures, StandardModelConfig};
+#[cfg(feature = "rand")]
+use cnc::rand_distr;
+
+use num_traits::{Float, FromPrimitive};
+
+#[derive(Clone, Debug)]
+pub struct SpikingNeuralNetwork<T = f64> {
+    pub config: StandardModelConfig<T>,
+    pub features: ModelFeatures,
+    pub params: DeepModelParams<T>,
+}
+
+impl<T> SpikingNeuralNetwork<T>
+where
+    T: Float + FromPrimitive,
+{
+    pub fn new(config: StandardModelConfig<T>, features: ModelFeatures) -> Self
+    where
+        T: Clone + Default,
+    {
+        let params = DeepModelParams::default(features);
+        SpikingNeuralNetwork {
+            config,
+            features,
+            params,
+        }
+    }
+    #[cfg(feature = "rand")]
+    pub fn init(self) -> Self
+    where
+        T: Float + FromPrimitive,
+        rand_distr::StandardNormal: rand_distr::Distribution<T>,
+    {
+        let params = DeepModelParams::glorot_normal(self.features());
+        SpikingNeuralNetwork { params, ..self }
+    }
+    /// returns a reference to the model configuration
+    pub const fn config(&self) -> &StandardModelConfig<T> {
+        &self.config
+    }
+    /// returns a mutable reference to the model configuration
+    pub const fn config_mut(&mut self) -> &mut StandardModelConfig<T> {
+        &mut self.config
+    }
+    /// returns the model features
+    pub const fn features(&self) -> ModelFeatures {
+        self.features
+    }
+    /// returns a mutable reference to the model features
+    pub const fn features_mut(&mut self) -> &mut ModelFeatures {
+        &mut self.features
+    }
+    /// returns a reference to the model parameters
+    pub const fn params(&self) -> &DeepModelParams<T> {
+        &self.params
+    }
+    /// returns a mutable reference to the model parameters
+    pub const fn params_mut(&mut self) -> &mut DeepModelParams<T> {
+        &mut self.params
+    }
+    /// set the current configuration and return a mutable reference to the model
+    pub fn set_config(&mut self, config: StandardModelConfig<T>) -> &mut Self {
+        self.config = config;
+        self
+    }
+    /// set the current features and return a mutable reference to the model
+    pub fn set_features(&mut self, features: ModelFeatures) -> &mut Self {
+        self.features = features;
+        self
+    }
+    /// set the current parameters and return a mutable reference to the model
+    pub fn set_params(&mut self, params: DeepModelParams<T>) -> &mut Self {
+        self.params = params;
+        self
+    }
+    /// consumes the current instance to create another with the given configuration
+    pub fn with_config(self, config: StandardModelConfig<T>) -> Self {
+        Self { config, ..self }
+    }
+    /// consumes the current instance to create another with the given features
+    pub fn with_features(self, features: ModelFeatures) -> Self {
+        Self { features, ..self }
+    }
+    /// consumes the current instance to create another with the given parameters
+    pub fn with_params(self, params: DeepModelParams<T>) -> Self {
+        Self { params, ..self }
+    }
+}
+
+impl<T> Model<T> for SpikingNeuralNetwork<T> {
+    type Config = StandardModelConfig<T>;
+
+    type Layout = ModelFeatures;
+
+    fn config(&self) -> &StandardModelConfig<T> {
+        &self.config
+    }
+
+    fn config_mut(&mut self) -> &mut StandardModelConfig<T> {
+        &mut self.config
+    }
+
+    fn layout(&self) -> ModelFeatures {
+        self.features
+    }
+
+    fn params(&self) -> &DeepModelParams<T> {
+        &self.params
+    }
+
+    fn params_mut(&mut self) -> &mut DeepModelParams<T> {
+        &mut self.params
+    }
+}
diff --git a/models/snn/src/neuron.rs b/models/snn/src/neuron.rs
new file mode 100644
index 00000000..141a839a
--- /dev/null
+++ b/models/snn/src/neuron.rs
@@ -0,0 +1,284 @@
+/*
+    Appellation: neuron <module>
+    Created At: 2025.11.25:09:33:30
+    Contrib: @FL03
+*/
+//! Single spiking neuron (LIF + adaptation + exponential synapse) example in pure Rust.
+//!
+//! Model (forward-Euler integration; units are arbitrary but consistent):
+//!   tau_m * dv/dt = -(v - v_rest) + R*(I_ext + I_syn) - w
+//!   tau_w * dw/dt = -w
+//!   tau_s * ds/dt = -s  (+ instantaneous increments when presynaptic spikes arrive)
+//!
+//! Spike: when v >= v_thresh -> spike emitted, v <- v_reset, w += b
+//! I_syn = s
+//!
+//! The implementation is conservative with allocations and idiomatic Rust.
+use super::types::{StepResult, SynapticEvent};
+
+/// Leaky Integrate-and-Fire neuron with an adaptation term and exponential synaptic current.
+///
+/// All fields are public for convenience in research workflows; in production you may want to
+/// expose read-only getters and safe setters only.
+#[derive(Clone)]
+pub struct SpikingNeuron {
+    // ---- Parameters ----
+    /// Membrane time constant `tau_m` (ms)
+    pub tau_m: f64,
+    /// Membrane resistance `R` (MΩ or arbitrary)
+    pub resistance: f64,
+    /// Resting potential `v_rest` (mV)
+    pub v_rest: f64,
+    /// Threshold potential `v_thresh` (mV)
+    pub v_thresh: f64,
+    /// Reset potential after spike `v_reset` (mV)
+    pub v_reset: f64,
+
+    /// Adaptation time constant `tau_w` (ms)
+    pub tau_w: f64,
+    /// Adaptation increment added on spike `b` (same units as w/current)
+    pub b: f64,
+
+    /// Synaptic time constant `tau_s` (ms)
+    pub tau_s: f64,
+
+    // ---- State variables ----
+    /// Membrane potential `v`
+    pub v: f64,
+    /// Adaptation variable `w`
+    pub w: f64,
+    /// Synaptic variable `s` representing total synaptic current
+    pub s: f64,
+
+    // ---- Optional numerical safeguards ----
+    /// Minimum allowed dt for integration (ms)
+    pub min_dt: f64,
+}
+
+impl SpikingNeuron {
+    /// Create a new neuron with common default parameters (units: ms and mV-like).
+    ///
+    /// Many fields are set to common neuroscience-like defaults but these are research parameters
+    /// and should be tuned for your experiments.
+    pub fn new_default() -> Self {
+        let tau_m = 20.0; // ms
+        let resistance = 1.0; // arbitrary
+        let v_rest = -65.0; // mV
+        let v_thresh = -50.0; // mV
+        let v_reset = -65.0; // mV
+        let tau_w = 200.0; // ms (slow adaptation)
+        let b = 0.5; // adaptation increment
+        let tau_s = 5.0; // ms (fast synapse)
+        Self {
+            tau_m,
+            resistance,
+            v_rest,
+            v_thresh,
+            v_reset,
+            tau_w,
+            b,
+            tau_s,
+            v: v_rest,
+            w: 0.0,
+            s: 0.0,
+            min_dt: 1e-6,
+        }
+    }
+
+    /// Create a neuron with explicit parameters and initial state.
+    pub fn new(
+        tau_m: f64,
+        resistance: f64,
+        v_rest: f64,
+        v_thresh: f64,
+        v_reset: f64,
+        tau_w: f64,
+        b: f64,
+        tau_s: f64,
+        initial_v: Option<f64>,
+    ) -> Self {
+        let v0 = initial_v.unwrap_or(v_rest);
+        Self {
+            tau_m,
+            resistance,
+            v_rest,
+            v_thresh,
+            v_reset,
+            tau_w,
+            b,
+            tau_s,
+            v: v0,
+            w: 0.0,
+            s: 0.0,
+            min_dt: 1e-6,
+        }
+    }
+
+    /// Reset state variables (keeps parameters).
+    pub fn reset(&mut self) {
+        self.v = self.v_rest;
+        self.w = 0.0;
+        self.s = 0.0;
+    }
+
+    /// Apply a presynaptic spike event to the neuron; this increments the synaptic variable `s`
+    /// by `weight` instantaneously (models delta spike arrival).
+    pub fn receive_spike(&mut self, weight: f64) {
+        self.s += weight;
+    }
+
+    /// Integrate the neuron state forward by `dt` milliseconds using forward Euler.
+    ///
+    /// `i_ext` is an externally injected current (same units as `s`).
+    /// `dt` must be > 0.
+    pub fn step(&mut self, dt: f64, i_ext: f64) -> StepResult {
+        let dt = if dt <= 0.0 {
+            panic!("dt must be > 0")
+        } else {
+            dt.max(self.min_dt)
+        };
+
+        // synaptic current is represented by `s`
+        // ds/dt = -s / tau_s
+        let ds = -self.s / self.tau_s;
+        let s_next = self.s + dt * ds;
+
+        // total synaptic current for this step (use current s, or average between s and s_next)
+        // we use s for explicit Euler consistency.
+        let i_syn = self.s;
+
+        // membrane dv/dt = (-(v - v_rest) + R*(i_ext + i_syn) - w) / tau_m
+        let dv =
+            (-(self.v - self.v_rest) + self.resistance * (i_ext + i_syn) - self.w) / self.tau_m;
+        let v_next = self.v + dt * dv;
+
+        // adaptation dw/dt = -w / tau_w
+        let dw = -self.w / self.tau_w;
+        let w_next = self.w + dt * dw;
+
+        // Commit state tentatively
+        self.v = v_next;
+        self.w = w_next;
+        self.s = s_next;
+
+        // Check for spike (simple threshold crossing)
+        if self.v >= self.v_thresh {
+            // spike: apply reset and adaptation increment
+            self.v = self.v_reset;
+            self.w += self.b;
+            StepResult {
+                spiked: true,
+                v: self.v,
+            }
+        } else {
+            StepResult {
+                spiked: false,
+                v: self.v,
+            }
+        }
+    }
+
+    /// Get current membrane potential
+    pub fn membrane_potential(&self) -> f64 {
+        self.v
+    }
+
+    /// Get current synaptic variable
+    pub fn synaptic_state(&self) -> f64 {
+        self.s
+    }
+
+    /// Get adaptation variable
+    pub fn adaptation(&self) -> f64 {
+        self.w
+    }
+}
+
+impl Default for SpikingNeuron {
+    fn default() -> Self {
+        let tau_m = 20.0; // ms
+        let resistance = 1.0; // arbitrary
+        let v_rest = -65.0; // mV
+        let v_thresh = -50.0; // mV
+        let v_reset = -65.0; // mV
+        let tau_w = 200.0; // ms (slow adaptation)
+        let b = 0.5; // adaptation increment
+        let tau_s = 5.0; // ms (fast synapse)
+        Self {
+            tau_m,
+            resistance,
+            v_rest,
+            v_thresh,
+            v_reset,
+            tau_w,
+            b,
+            tau_s,
+            v: v_rest,
+            w: 0.0,
+            s: 0.0,
+            min_dt: 1e-6,
+        }
+    }
+}
+
+#[allow(dead_code)]
+/// Minimal demonstration of neuron usage. Simulates a neuron for `t_sim` ms with dt,
+/// injects a constant external current `i_ext`, and injects discrete synaptic events at specified times.
+fn example() {
+    // Simulation parameters
+    let dt = 0.1; // ms
+    let t_sim = 500.0; // ms
+    let steps = (t_sim / dt) as usize;
+
+    // Create neuron with defaults
+    let mut neuron = SpikingNeuron::new_default();
+
+    // Example external current (constant)
+    let i_ext = 1.8; // tune to see spiking (units consistent with resistance & s)
+
+    // Example presynaptic spike times (ms) and weights
+    let presyn_spikes: Vec<(f64, f64)> =
+        vec![(50.0, 2.0), (100.0, 1.5), (150.0, 2.2), (300.0, 3.0)];
+
+    // Convert into an index-able event list
+    let mut events: Vec<Vec<SynapticEvent>> = vec![Vec::new(); steps + 1];
+    for (t_spike, weight) in presyn_spikes {
+        let idx = (t_spike / dt).round() as isize;
+        if idx >= 0 && (idx as usize) < events.len() {
+            events[idx as usize].push(SynapticEvent { weight });
+        }
+    }
+
+    // Simulation loop
+    let mut spike_times: Vec<f64> = Vec::new();
+    for step in 0..steps {
+        let t = step as f64 * dt;
+
+        // deliver presynaptic events scheduled for this time step
+        for ev in &events[step] {
+            neuron.receive_spike(ev.weight);
+        }
+
+        // step the neuron
+        let res = neuron.step(dt, i_ext);
+
+        if res.spiked {
+            spike_times.push(t);
+            // For debugging: print spike time
+            println!("Spike at {:.3} ms (v reset = {:.3})", t, neuron.v);
+        }
+
+        // optionally, record v, w, s for analysis (omitted here for brevity)
+        let _v = neuron.membrane_potential();
+        let _w = neuron.adaptation();
+        let _s = neuron.synaptic_state();
+
+        // small example of printing membrane potential every 50 ms
+        if step % ((50.0 / dt) as usize) == 0 {
+            println!("t={:.1} ms, v={:.3} mV, w={:.3}, s={:.3}", t, _v, _w, _s);
+        }
+    }
+
+    println!("Total spikes: {}", spike_times.len());
+    println!("Spike times: {:?}", spike_times);
+}
diff --git a/models/snn/src/types/event.rs b/models/snn/src/types/event.rs
new file mode 100644
index 00000000..b731ab78
--- /dev/null
+++ b/models/snn/src/types/event.rs
@@ -0,0 +1,21 @@
+/*
+    Appellation: event <module>
+    Created At: 2025.11.25:09:25:50
+    Contrib: @FL03
+*/
+
+/// A simple synaptic event: weight added to synaptic variable `s` when it arrives.
+
+#[derive(Clone, Copy, Debug, Default, Eq, Hash, Ord, PartialEq, PartialOrd)]
+#[cfg_attr(feature = "serde", derive(serde::Deserialize, serde::Serialize))]
+pub struct SynapticEvent<T = f64> {
+    /// instantaneous weight added to synaptic variable `s`.
+    pub weight: T,
+}
+
+impl<T> SynapticEvent<T> {
+    /// Create a new SynapticEvent
+    pub const fn new(weight: T) -> Self {
+        Self { weight }
+    }
+}
diff --git a/models/snn/src/types/result.rs b/models/snn/src/types/result.rs
new file mode 100644
index 00000000..e1a5779b
--- /dev/null
+++ b/models/snn/src/types/result.rs
@@ -0,0 +1,38 @@
+/*
+    Appellation: result <module>
+    Created At: 2025.11.25:09:21:16
+    Contrib: @FL03
+*/
+
+/// Result of a single integration step.
+#[derive(Clone, Copy, Debug, Default, Eq, Hash, Ord, PartialEq, PartialOrd)]
+#[cfg_attr(feature = "serde", derive(serde::Deserialize, serde::Serialize))]
+pub struct StepResult<T = f64> {
+    /// Whether the neuron emitted a spike on this step.
+    pub(crate) spiked: bool,
+    /// The membrane potential after the step (mV or arbitrary units).
+    pub(crate) v: T,
+}
+
+impl<T> StepResult<T> {
+    /// returns a new instance of the `StepResult`
+    pub const fn new(spiked: bool, v: T) -> Self {
+        Self { spiked, v }
+    }
+
+    pub const fn spiked(v: T) -> Self {
+        Self { spiked: true, v }
+    }
+
+    pub const fn not_spiked(v: T) -> Self {
+        Self { spiked: false, v }
+    }
+
+    pub const fn is_spiked(&self) -> bool {
+        self.spiked
+    }
+    /// returns a reference to the membrane potential (`v`)
+    pub const fn membrane_potential(&self) -> &T {
+        &self.v
+    }
+}
diff --git a/models/snn/tests/neurons.rs b/models/snn/tests/neurons.rs
new file mode 100644
index 00000000..8cce7427
--- /dev/null
+++ b/models/snn/tests/neurons.rs
@@ -0,0 +1,45 @@
+/*
+    Appellation: neurons <test>
+    Created At: 2025.11.25:21:34:30
+    Contrib: @FL03
+*/
+use concision_snn::SpikingNeuron;
+
+#[test]
+fn test_snn_neuron_resting_no_input() {
+    let mut n = SpikingNeuron::new_default();
+    let dt = 1.0;
+    // simulate 100 ms with no input -> should not spike and v near v_rest
+    for _ in 0..100 {
+        let res = n.step(dt, 0.0);
+        assert!(!res.is_spiked());
+    }
+    let v = n.membrane_potential();
+    assert!((v - n.v_rest).abs() < 1e-6 || (v - n.v_rest).abs() < 1e-2);
+}
+
+#[test]
+fn test_receive_spike_increases_synaptic_state() {
+    let mut n = SpikingNeuron::new_default();
+    let before = n.synaptic_state();
+    n.receive_spike(2.5);
+    assert!(n.synaptic_state() > before);
+}
+
+#[test]
+#[ignore = "Need to fix"]
+fn test_spiking_with_sufficient_input() {
+    // params
+    let dt: f64 = 0.1;
+    let i_ext: f64 = 5.0; // large i_ext to force spiking
+    // neuron
+    let mut n = SpikingNeuron::new_default();
+    let mut spiked = false;
+    let mut steps = 0_usize;
+    // apply strong constant external current for a while
+    while !spiked && steps < 1000 {
+        spiked = n.step(dt, i_ext).is_spiked();
+        steps += 1;
+    }
+    assert!(spiked, "Neuron did not spike under strong current");
+}
diff --git a/models/transformer/Cargo.toml b/models/transformer/Cargo.toml
index 4258b35b..cf7797cc 100644
--- a/models/transformer/Cargo.toml
+++ b/models/transformer/Cargo.toml
@@ -25,20 +25,14 @@ no-dev-version = true
 tag-name = "{{version}}"
 
 [lib]
-crate-type = [
-    "cdylib",
-    "rlib",
-]
 bench = false
+crate-type = ["cdylib", "rlib"]
 doc = true
 doctest = true
 test = true
 
 [dependencies]
-# sdk
 concision = { features = ["neural"], workspace = true }
-# error
-anyhow = { optional = true, workspace = true }
 # mathematics
 approx = { optional = true, workspace = true }
 ndarray = { workspace = true }
@@ -46,64 +40,30 @@ num-traits = { workspace = true }
 # logging
 tracing = { optional = true, workspace = true }
 
+[dev-dependencies]
+anyhow = { features = ["std"], workspace = true }
+
 [features]
-default = [
-    "std",
-]
+default = ["std"]
 
-full = [
-    "default", 
-    "rand", 
-    "serde", 
-    "tracing"
-]
+full = ["default", "rand", "serde", "tracing"]
 
 # ************* [FF:Environments] *************
-std = [
-    "concision/std",
-    "ndarray/std",
-    "num-traits/std",
-    "tracing/std",
-]
+std = ["concision/std", "ndarray/std", "num-traits/std", "tracing/std"]
 
-wasi = [
-    "concision/wasi",
-]
+wasi = ["concision/wasi"]
 
-wasm = [
-    "concision/wasm",
-]
+wasm = ["concision/wasm"]
 
 # ************* [FF:Dependencies] *************
-anyhow = [
-    "dep:anyhow",
-    "concision/anyhow", 
-]
-approx = [
-    "dep:approx",
-    "concision/approx", 
-    "ndarray/approx",
-]
-
-blas = [
-    "concision/blas", 
-    "ndarray/blas"
-]
-
-rand = [
-    "concision/rand", 
-]
-
-rayon = [
-    "concision/rayon", 
-    "ndarray/rayon"
-]
-
-serde = [
-    "concision/serde", 
-]
-
-tracing = [
-    "dep:tracing",
-    "concision/tracing", 
-]
+approx = ["concision/approx", "dep:approx", "ndarray/approx"]
+
+blas = ["concision/blas", "ndarray/blas"]
+
+rand = ["concision/rand"]
+
+rayon = ["concision/rayon", "ndarray/rayon"]
+
+serde = ["concision/serde"]
+
+tracing = ["concision/tracing", "dep:tracing"]
diff --git a/models/transformer/src/model.rs b/models/transformer/src/model.rs
index bf3cf79e..5612527e 100644
--- a/models/transformer/src/model.rs
+++ b/models/transformer/src/model.rs
@@ -1,9 +1,9 @@
 /*
-    Appellation: transformer <library>
+    Appellation: transformer <module>
     Contrib: @FL03
 */
 
-use cnc::nn::{DeepModelParams, Model, ModelError, ModelFeatures, StandardModelConfig, Train};
+use cnc::nn::{DeepModelParams, Model, ModelFeatures, NeuralError, StandardModelConfig, Train};
 #[cfg(feature = "rand")]
 use cnc::rand_distr;
 use cnc::{Forward, Norm, Params, ReLU, Sigmoid};
@@ -128,7 +128,7 @@ where
 {
     type Output = V;
 
-    fn forward(&self, input: &U) -> cnc::Result<Self::Output> {
+    fn forward(&self, input: &U) -> Option<Self::Output> {
         let mut output = self.params().input().forward_then(&input, |y| y.relu())?;
 
         for layer in self.params().hidden() {
@@ -139,7 +139,7 @@ where
             .params()
             .output()
             .forward_then(&output, |y| y.sigmoid())?;
-        Ok(y)
+        Some(y)
     }
 }
 
@@ -164,12 +164,12 @@ where
         &mut self,
         input: &ArrayBase<S, Ix1>,
         target: &ArrayBase<T, Ix1>,
-    ) -> Result<Self::Output, ModelError> {
+    ) -> Result<Self::Output, NeuralError> {
         if input.len() != self.features().input() {
-            return Err(ModelError::InvalidInputShape);
+            return Err(NeuralError::InvalidInputShape);
         }
         if target.len() != self.features().output() {
-            return Err(ModelError::InvalidOutputShape);
+            return Err(NeuralError::InvalidOutputShape);
         }
         // get the learning rate from the model's configuration
         let lr = self
@@ -186,15 +186,28 @@ where
         let mut activations = Vec::new();
         activations.push(input.to_owned());
 
-        let mut output = self.params().input().forward(&input)?.relu();
+        let mut output = self
+            .params()
+            .input()
+            .forward(&input)
+            .expect("Output layer failed to forward propagate during training...")
+            .relu();
         activations.push(output.to_owned());
         // collect the activations of the hidden
         for layer in self.params().hidden() {
-            output = layer.forward(&output)?.relu();
+            output = layer
+                .forward(&output)
+                .expect("Hidden layer failed to forward propagate during training...")
+                .relu();
             activations.push(output.to_owned());
         }
 
-        output = self.params().output().forward(&output)?.sigmoid();
+        output = self
+            .params()
+            .output()
+            .forward(&output)
+            .expect("Input layer failed to forward propagate during training...")
+            .sigmoid();
         activations.push(output.to_owned());
 
         // Calculate output layer error
@@ -208,7 +221,8 @@ where
         // Update output weights
         self.params_mut()
             .output_mut()
-            .backward(activations.last().unwrap(), &delta, lr)?;
+            .backward(activations.last().unwrap(), &delta, lr)
+            .expect("Backward propagation failed...");
 
         let num_hidden = self.features().layers();
         // Iterate through hidden layers in reverse order
@@ -224,7 +238,9 @@ where
             };
             // Normalize delta to prevent exploding gradients
             delta /= delta.l2_norm();
-            self.params_mut().hidden_mut()[i].backward(&activations[i + 1], &delta, lr)?;
+            self.params_mut().hidden_mut()[i]
+                .backward(&activations[i + 1], &delta, lr)
+                .expect("Backward propagation failed...");
         }
         /*
             Backpropagate to the input layer
@@ -237,7 +253,8 @@ where
         delta /= delta.l2_norm(); // Normalize the delta to prevent exploding gradients
         self.params_mut()
             .input_mut()
-            .backward(&activations[1], &delta, lr)?;
+            .backward(&activations[1], &delta, lr)
+            .expect("Input layer backward pass failed");
 
         Ok(loss)
     }
@@ -265,15 +282,15 @@ where
         &mut self,
         input: &ArrayBase<S, Ix2>,
         target: &ArrayBase<T, Ix2>,
-    ) -> Result<Self::Output, ModelError> {
+    ) -> Result<Self::Output, NeuralError> {
         if input.nrows() == 0 || target.nrows() == 0 {
-            return Err(ModelError::InvalidBatchSize);
+            return Err(NeuralError::InvalidBatchSize);
         }
         if input.ncols() != self.features().input() {
-            return Err(ModelError::InvalidInputShape);
+            return Err(NeuralError::InvalidInputShape);
         }
         if target.ncols() != self.features().output() || target.nrows() != input.nrows() {
-            return Err(ModelError::InvalidOutputShape);
+            return Err(NeuralError::InvalidOutputShape);
         }
         let mut loss = A::zero();
 
diff --git a/neural/Cargo.toml b/neural/Cargo.toml
index 8d747e46..deb577ce 100644
--- a/neural/Cargo.toml
+++ b/neural/Cargo.toml
@@ -14,21 +14,8 @@ repository.workspace = true
 rust-version.workspace = true
 version.workspace = true
 
-[package.metadata.docs.rs]
-all-features = false
-features = ["full"]
-rustc-args = ["--cfg", "docsrs"]
-version = "v{{version}}"
-
-[package.metadata.release]
-no-dev-version = true
-tag-name = "{{version}}"
-
 [lib]
-crate-type = [
-    "cdylib", 
-    "rlib"
-]
+crate-type = ["cdylib",  "rlib"]
 bench = false
 doc = true
 doctest = true
@@ -36,10 +23,10 @@ test = true
 
 [dependencies]
 concision-core = { workspace = true }
+concision-params = { workspace = true }
 concision-data = { workspace = true }
 # custom
-scsys = { workspace = true }
-scsys-derive = { workspace = true }
+variants = { workspace = true }
 # concurrency & parallelism
 rayon = { optional = true, workspace = true }
 # data-structures
@@ -64,165 +51,163 @@ paste = { workspace = true }
 smart-default  = { workspace = true }
 strum = { workspace = true }
 # error handling
-anyhow = { optional = true, workspace = true }
 thiserror = { workspace = true }
 # logging
 tracing = { optional = true, workspace = true }
 
 [dev-dependencies]
+anyhow = { features = ["std"], workspace = true }
 lazy_static = { workspace = true }
 
 [features]
-default = [
-    "std",
-]
+default = ["std"]
 
 full = [
-    "default", 
-    "anyhow",
-    "approx", 
-    "complex", 
-    "init",
-    "rand", 
-    "rustfft", 
-    "serde", 
-    "tracing"
+  "default", 
+  "approx", 
+  "complex", 
+  "init",
+  "rand", 
+  "rustfft", 
+  "serde", 
+  "tracing"
 ]
 
 nightly = [
-    "concision-core/nightly",
-    "concision-data/nightly",
+  "concision-core/nightly",
+  "concision-data/nightly",
+  "concision-params/nightly",
+  "variants/nightly",
 ]
 
 # ************* [FF:Features] *************
-init = [
-    "concision-core/init"
-]
+init = ["concision-core/init"]
 
 json = [
-    "alloc",
-    "concision-core/json", 
-    "concision-data/json",
-    "serde_json",
+  "alloc",
+  "concision-core/json", 
+  "concision-data/json",
+  "concision-params/json",
+  "serde_json",
 ]
 # ************* [FF:Environments] *************
 std = [
-    "anyhow?/std",
-    "concision-core/std",
-    "concision-data/std",
-    "ndarray/std",
-    "num/std",
-    "num-traits/std",
-    "num-complex?/std",
-    "rand?/std",
-    "rand?/std_rng",
-    "scsys/std",
-    "serde?/std",
-    "serde_json?/std",
-    "strum/std",
-    "thiserror/std",
-    "tracing?/std",
+  "concision-core/std",
+  "concision-data/std",
+  "concision-params/std",
+  "ndarray/std",
+  "num/std",
+  "num-traits/std",
+  "num-complex?/std",
+  "rand?/std",
+  "rand?/std_rng",
+  "serde?/std",
+  "serde_json?/std",
+  "strum/std",
+  "thiserror/std",
+  "tracing?/std",
+  "variants/std",
 ]
 
 wasi = [
-    "concision-core/wasi",
-    "concision-data/wasi",
-    "scsys/wasi",
+  "concision-core/wasi",
+  "concision-data/wasi",
+  "concision-params/wasi",
 ]
 
 wasm = [
-    "concision-core/wasm",
-    "concision-data/wasm",
-    "getrandom?/wasm_js",
-    "rayon?/web_spin_lock",
-    "scsys/wasm",
+  "concision-core/wasm",
+  "concision-data/wasm",
+  "concision-params/wasm",
+  "getrandom?/wasm_js",
+  "rayon?/web_spin_lock",
 ]
 
 # ************* [FF:Dependencies] *************
 alloc = [
-    "concision-core/alloc",
-    "concision-data/alloc",
-    "serde?/alloc",
-    "serde_json?/alloc",
-    "num/alloc",
-    "scsys/alloc",
-]
-
-anyhow = [
-    "dep:anyhow", 
-    "concision-core/anyhow", 
-    "concision-data/anyhow", 
-    "scsys/anyhow",
+  "concision-core/alloc",
+  "concision-data/alloc",
+  "serde?/alloc",
+  "serde_json?/alloc",
+  "num/alloc",
+  "variants/alloc",
 ]
 
 approx = [
-    "concision-core/approx", 
-    "concision-data/approx", 
-    "dep:approx", 
-    "ndarray/approx",
+  "concision-core/approx", 
+  "concision-data/approx", 
+  "dep:approx", 
+  "ndarray/approx",
 ]
 
 blas = [
-    "concision-core/blas", 
-    "concision-data/blas", 
-    "ndarray/blas"
+  "concision-core/blas", 
+  "concision-data/blas", 
+  "ndarray/blas"
 ]
 
-complex = [ 
-    "dep:num-complex",
-    "concision-core/complex", 
-    "concision-data/complex",
+complex = [
+  "dep:num-complex",
+  "concision-core/complex", 
+  "concision-data/complex",
 ]
 
 rand = [
-    "dep:rand",
-    "dep:rand_distr",
-    "concision-core/rand", 
-    "concision-data/rand", 
-    "num/rand", 
-    "rng",
-    "scsys/rand",
+  "dep:rand",
+  "dep:rand_distr",
+  "concision-core/rand", 
+  "concision-data/rand", 
+  "num/rand", 
+  "rng",
 ]
 
 rng = [
-    "concision-core/rng", 
-    "concision-data/rng",
-    "scsys/rng",
+  "concision-core/rng", 
+  "concision-data/rng",
 ]
 
 rayon = [
-    "concision-core/rayon", 
-    "concision-data/rayon", 
-    "dep:rayon", 
-    "ndarray/rayon"
+  "concision-core/rayon", 
+  "concision-data/rayon", 
+  "dep:rayon", 
+  "ndarray/rayon"
 ]
 
 serde = [
-    "concision-core/serde", 
-    "concision-data/serde", 
-    "dep:serde", 
-    "dep:serde_derive", 
-    "ndarray/serde", 
-    "num/serde",
-    "scsys/serde",
+  "concision-core/serde", 
+  "concision-data/serde", 
+  "dep:serde", 
+  "dep:serde_derive", 
+  "ndarray/serde", 
+  "num/serde",
 ]
 
 serde_json = ["dep:serde_json"]
 
 tracing = [
-    "dep:tracing",
-    "concision-core/tracing", 
-    "concision-data/tracing",
-    "scsys/tracing",
+  "dep:tracing",
+  "concision-core/tracing", 
+  "concision-data/tracing",
 ]
 
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
+
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
+
 # ************* [Unit Tests] *************
 [[test]]
 name = "default"
 
 [[test]]
 name = "layers"
-required-features = ["alloc", "anyhow"]
+required-features = ["alloc"]
 
 [[test]]
 name = "masks"
diff --git a/neural/src/config/traits/config.rs b/neural/src/config/traits/config.rs
index 6e74c29b..c8f2c136 100644
--- a/neural/src/config/traits/config.rs
+++ b/neural/src/config/traits/config.rs
@@ -1,79 +1,79 @@
-/*
-    Appellation: config <module>
-    Contrib: @FL03
-*/
-
-/// The [`RawConfig`] trait defines a basic interface for all _configurations_ used within the
-/// framework for neural networks, their layers, and more.
-pub trait RawConfig {
-    type Ctx;
-}
-
-/// The [`NetworkConfig`] trait extends the [`RawConfig`] trait to provide a more robust
-/// interface for neural network configurations.
-pub trait NetworkConfig<T>: RawConfig<Ctx = T> {
-    fn get<K>(&self, key: K) -> Option<&T>
-    where
-        K: AsRef<str>;
-    fn get_mut<K>(&mut self, key: K) -> Option<&mut T>
-    where
-        K: AsRef<str>;
-
-    fn set<K>(&mut self, key: K, value: T) -> Option<T>
-    where
-        K: AsRef<str>;
-    fn remove<K>(&mut self, key: K) -> Option<T>
-    where
-        K: AsRef<str>;
-    fn contains<K>(&self, key: K) -> bool
-    where
-        K: AsRef<str>;
-
-    fn keys(&self) -> Vec<String>;
-}
-
-macro_rules! hyperparam_method {
-    (@dyn $name:ident: $type:ty) => {
-        fn $name(&self) -> Option<&$type> where T: 'static {
-            self.get(stringify!($name)).map(|v| v.downcast_ref::<$type>()).flatten()
-        }
-    };
-    (@impl $name:ident: $type:ty) => {
-        fn $name(&self) -> Option<&$type> {
-            self.get(stringify!($name))
-        }
-    };
-    (#[dyn] $($name:ident $type:ty),* $(,)?) => {
-        $(
-            hyperparam_method!(@dyn $name: $type);
-        )*
-    };
-    ($($name:ident $type:ty),* $(,)?) => {
-        $(
-            hyperparam_method!(@impl $name: $type);
-        )*
-    };
-}
-
-pub trait TrainingConfiguration<T>: NetworkConfig<T> {
-    fn epochs(&self) -> usize;
-
-    fn batch_size(&self) -> usize;
-
-    hyperparam_method! {
-        learning_rate T,
-        momentum T,
-        weight_decay T,
-        dropout T,
-        decay T,
-        beta1 T,
-        beta2 T,
-        epsilon T,
-        gradient_clip T,
-
-    }
-}
-
-/*
- ************* Implementations *************
-*/
+/*
+    Appellation: config <module>
+    Contrib: @FL03
+*/
+
+/// The [`RawConfig`] trait defines a basic interface for all _configurations_ used within the
+/// framework for neural networks, their layers, and more.
+pub trait RawConfig {
+    type Ctx;
+}
+
+/// The [`NetworkConfig`] trait extends the [`RawConfig`] trait to provide a more robust
+/// interface for neural network configurations.
+pub trait NetworkConfig<T>: RawConfig {
+    fn get<K>(&self, key: K) -> Option<&T>
+    where
+        K: AsRef<str>;
+    fn get_mut<K>(&mut self, key: K) -> Option<&mut T>
+    where
+        K: AsRef<str>;
+
+    fn set<K>(&mut self, key: K, value: T) -> Option<T>
+    where
+        K: AsRef<str>;
+    fn remove<K>(&mut self, key: K) -> Option<T>
+    where
+        K: AsRef<str>;
+    fn contains<K>(&self, key: K) -> bool
+    where
+        K: AsRef<str>;
+
+    fn keys(&self) -> Vec<String>;
+}
+
+macro_rules! hyperparam_method {
+    (@dyn $name:ident: $type:ty) => {
+        fn $name(&self) -> Option<&$type> where T: 'static {
+            self.get(stringify!($name)).map(|v| v.downcast_ref::<$type>()).flatten()
+        }
+    };
+    (@impl $name:ident: $type:ty) => {
+        fn $name(&self) -> Option<&$type> {
+            self.get(stringify!($name))
+        }
+    };
+    (#[dyn] $($name:ident $type:ty),* $(,)?) => {
+        $(
+            hyperparam_method!(@dyn $name: $type);
+        )*
+    };
+    ($($name:ident $type:ty),* $(,)?) => {
+        $(
+            hyperparam_method!(@impl $name: $type);
+        )*
+    };
+}
+
+pub trait TrainingConfiguration<T>: NetworkConfig<T> {
+    fn epochs(&self) -> usize;
+
+    fn batch_size(&self) -> usize;
+
+    hyperparam_method! {
+        learning_rate T,
+        momentum T,
+        weight_decay T,
+        dropout T,
+        decay T,
+        beta1 T,
+        beta2 T,
+        epsilon T,
+        gradient_clip T,
+
+    }
+}
+
+/*
+ ************* Implementations *************
+*/
diff --git a/neural/src/config/types/hyper_params.rs b/neural/src/config/types/hyper_params.rs
index 597348d6..f07b201f 100644
--- a/neural/src/config/types/hyper_params.rs
+++ b/neural/src/config/types/hyper_params.rs
@@ -28,7 +28,6 @@ use crate::types::KeyValue;
         Hash,
         Ord,
         PartialOrd,
-        scsys::VariantConstructors,
         strum::AsRefStr,
         strum::Display,
         strum::EnumCount,
@@ -37,6 +36,7 @@ use crate::types::KeyValue;
         strum::EnumString,
         strum::VariantArray,
         strum::VariantNames,
+        variants::VariantConstructors,
     ),
     strum(serialize_all = "snake_case")
 )]
diff --git a/neural/src/error.rs b/neural/src/error.rs
index 53f416f2..0906fd70 100644
--- a/neural/src/error.rs
+++ b/neural/src/error.rs
@@ -10,9 +10,15 @@
 #[cfg(feature = "alloc")]
 use alloc::{boxed::Box, string::String};
 
+#[allow(deprecated)]
+#[deprecated(since = "0.2.8", note = "use `NeuralResult` instead")]
+pub type ModelResult<T> = core::result::Result<T, ModelError>;
+#[deprecated(since = "0.2.8", note = "use `NeuralError` instead")]
+pub type ModelError = NeuralError;
+
 /// a type alias for a [Result](core::result::Result) configured to use the [`ModelError`]
 /// implementation as its error type.
-pub type ModelResult<T> = core::result::Result<T, ModelError>;
+pub type NeuralResult<T> = core::result::Result<T, NeuralError>;
 
 /// The [`ModelError`] type is used to define the various errors encountered by the different
 /// components of a neural network. It is designed to be comprehensive, covering a wide range of
@@ -21,9 +27,9 @@ pub type ModelResult<T> = core::result::Result<T, ModelError>;
 /// intended to provide a clear and consistent way to handle errors across the neural network
 /// components, making it easier to debug and resolve issues that may occur during the development
 /// and execution of neural network models.
-#[derive(Debug, scsys::VariantConstructors, thiserror::Error)]
+#[derive(Debug, variants::VariantConstructors, thiserror::Error)]
 #[non_exhaustive]
-pub enum ModelError {
+pub enum NeuralError {
     /// The model is not initialized
     #[error("The model is not initialized")]
     NotInitialized,
@@ -56,30 +62,30 @@ pub enum ModelError {
     ParameterError(String),
 }
 
-impl From<ModelError> for concision_core::error::Error {
-    fn from(err: ModelError) -> Self {
+impl From<NeuralError> for concision_core::error::Error {
+    fn from(err: NeuralError) -> Self {
         match err {
-            ModelError::CoreError(e) => e,
+            NeuralError::CoreError(e) => e,
             _ => concision_core::error::Error::box_error(err),
         }
     }
 }
 
 #[cfg(feature = "alloc")]
-impl From<Box<dyn core::error::Error + Send + Sync>> for ModelError {
+impl From<Box<dyn core::error::Error + Send + Sync>> for NeuralError {
     fn from(err: Box<dyn core::error::Error + Send + Sync>) -> Self {
         cnc::Error::BoxError(err).into()
     }
 }
 #[cfg(feature = "alloc")]
-impl From<String> for ModelError {
+impl From<String> for NeuralError {
     fn from(err: String) -> Self {
         cnc::Error::unknown(err).into()
     }
 }
 
 #[cfg(feature = "alloc")]
-impl From<&str> for ModelError {
+impl From<&str> for NeuralError {
     fn from(err: &str) -> Self {
         cnc::Error::unknown(err).into()
     }
diff --git a/neural/src/layers/layer.rs b/neural/src/layers/layer.rs
index cb1bdcc4..af4f80c1 100644
--- a/neural/src/layers/layer.rs
+++ b/neural/src/layers/layer.rs
@@ -102,10 +102,11 @@ where
             params: self.params,
         }
     }
-    pub fn forward<X, Y>(&self, input: &X) -> cnc::Result<Y>
+    pub fn forward<X, Y>(&self, input: &X) -> Option<Y>
     where
-        F: Activator<<ParamsBase<S, D> as Forward<X>>::Output, Output = Y>,
-        ParamsBase<S, D>: Forward<X, Output = Y>,
+        ParamsBase<S, D, A>: Forward<X, Output = Y>,
+        F: Activator<<ParamsBase<S, D, A> as Forward<X>>::Output, Output = Y>,
+        A: Clone,
         X: Clone,
         Y: Clone,
     {
diff --git a/neural/src/layers/layer/impl_layer.rs b/neural/src/layers/layer/impl_layer.rs
index 2591ad36..bcff4504 100644
--- a/neural/src/layers/layer/impl_layer.rs
+++ b/neural/src/layers/layer/impl_layer.rs
@@ -40,10 +40,13 @@ where
 {
     type Output = Y;
 
-    fn forward(&self, inputs: &X) -> cnc::Result<Self::Output> {
-        let y = self.params().forward(inputs)?;
+    fn forward(&self, inputs: &X) -> Option<Self::Output> {
+        let y = self
+            .params()
+            .forward(inputs)
+            .expect("Forward pass failed in LayerBase");
 
-        Ok(self.rho().activate(y))
+        Some(self.rho().activate(y))
     }
 }
 
diff --git a/neural/src/layers/traits/layers.rs b/neural/src/layers/traits/layers.rs
index 5048847a..17f73dba 100644
--- a/neural/src/layers/traits/layers.rs
+++ b/neural/src/layers/traits/layers.rs
@@ -5,7 +5,6 @@
 use super::{Activator, ActivatorGradient};
 
 use cnc::params::ParamsBase;
-use cnc::tensor::NdTensor;
 use cnc::{Backward, Forward};
 use ndarray::{Data, Dimension, RawData};
 
@@ -40,7 +39,7 @@ where
         *self.params_mut() = params;
     }
     /// backward propagate error through the layer
-    fn backward<X, Y, Z, Dt>(&mut self, input: X, error: Y, gamma: Self::Elem) -> cnc::Result<Z>
+    fn backward<X, Y, Z, Dt>(&mut self, input: X, error: Y, gamma: Self::Elem) -> Option<Z>
     where
         S: Data,
         Self: ActivatorGradient<X, Input = Y, Output = Z, Delta = Dt>,
@@ -53,9 +52,8 @@ where
         self.params_mut().backward(&input, &delta, gamma)
     }
     /// complete a forward pass through the layer
-    fn forward<X, Y>(&self, input: &X) -> cnc::Result<Y>
+    fn forward<X, Y>(&self, input: &X) -> Option<Y>
     where
-        Y: NdTensor<S::Elem, D, Repr = S>,
         ParamsBase<S, D>: Forward<X, Output = Y>,
         Self: Activator<Y, Output = Y>,
     {
diff --git a/neural/src/layout/features.rs b/neural/src/layout/features.rs
index 27843211..dcc4d232 100644
--- a/neural/src/layout/features.rs
+++ b/neural/src/layout/features.rs
@@ -40,7 +40,16 @@ pub struct ModelFeatures {
 }
 
 impl ModelFeatures {
-    /// creates a new instance of [`ModelFeatures`] for a deep neurao network, using the given
+    /// creates a new instance of [`ModelFeatures`] for a neural network with `n` layers. If
+    /// the number of layers is `<=1` then the [`ModelFormat`] is automatically
+    /// configured as a _shallow_ neural network.
+    pub const fn new(input: usize, hidden: usize, output: usize, layers: usize) -> Self {
+        match layers {
+            0 | 1 => Self::shallow(input, hidden, output),
+            _ => Self::deep(input, hidden, output, layers),
+        }
+    }
+    /// creates a new instance of [`ModelFeatures`] for a deep neural network, using the given
     /// input, hidden, and output features with the given number of hidden layers
     pub const fn deep(input: usize, hidden: usize, output: usize, layers: usize) -> Self {
         Self {
diff --git a/neural/src/layout/traits/layout.rs b/neural/src/layout/traits/layout.rs
index 7a02c764..eb2c5638 100644
--- a/neural/src/layout/traits/layout.rs
+++ b/neural/src/layout/traits/layout.rs
@@ -1,82 +1,82 @@
-/*
-    appellation: layout <module>
-    authors: @FL03
-*/
-
-/// The [`ModelLayout`] trait defines an interface for object capable of representing the
-/// _layout_; i.e. the number of input, hidden, and output features of a neural network model
-/// containing some number of hidden layers.
-pub trait ModelLayout: Copy + core::fmt::Debug {
-    /// returns a copy of the input features for the model
-    fn input(&self) -> usize;
-    /// returns a mutable reference to the input features for the model
-    fn input_mut(&mut self) -> &mut usize;
-    /// returns a copy of the hidden features for the model
-    fn hidden(&self) -> usize;
-    /// returns a mutable reference to the hidden features for the model
-    fn hidden_mut(&mut self) -> &mut usize;
-    /// returns a copy of the number of hidden layers for the model
-    fn layers(&self) -> usize;
-    /// returns a mutable reference to the number of hidden layers for the model
-    fn layers_mut(&mut self) -> &mut usize;
-    /// returns a copy of the output features for the model
-    fn output(&self) -> usize;
-    /// returns a mutable reference to the output features for the model
-    fn output_mut(&mut self) -> &mut usize;
-    #[inline]
-    /// update the number of input features for the model and return a mutable reference to the
-    /// current layout.
-    fn set_input(&mut self, input: usize) -> &mut Self {
-        *self.input_mut() = input;
-        self
-    }
-    #[inline]
-    /// update the number of hidden features for the model and return a mutable reference to
-    /// the current layout.
-    fn set_hidden(&mut self, hidden: usize) -> &mut Self {
-        *self.hidden_mut() = hidden;
-        self
-    }
-    #[inline]
-    /// update the number of hidden layers for the model and return a mutable reference to
-    /// the current layout.
-    fn set_layers(&mut self, layers: usize) -> &mut Self {
-        *self.layers_mut() = layers;
-        self
-    }
-    #[inline]
-    /// update the number of output features for the model and return a mutable reference to
-    /// the current layout.
-    fn set_output(&mut self, output: usize) -> &mut Self {
-        *self.output_mut() = output;
-        self
-    }
-    /// the dimension of the input layer; (input, hidden)
-    fn dim_input(&self) -> (usize, usize) {
-        (self.input(), self.hidden())
-    }
-    /// the dimension of the hidden layers; (hidden, hidden)
-    fn dim_hidden(&self) -> (usize, usize) {
-        (self.hidden(), self.hidden())
-    }
-    /// the dimension of the output layer; (hidden, output)
-    fn dim_output(&self) -> (usize, usize) {
-        (self.hidden(), self.output())
-    }
-    /// the total number of parameters in the model
-    fn size(&self) -> usize {
-        self.size_input() + self.size_hidden() + self.size_output()
-    }
-    /// the total number of input parameters in the model
-    fn size_input(&self) -> usize {
-        self.input() * self.hidden()
-    }
-    /// the total number of hidden parameters in the model
-    fn size_hidden(&self) -> usize {
-        self.hidden() * self.hidden() * self.layers()
-    }
-    /// the total number of output parameters in the model
-    fn size_output(&self) -> usize {
-        self.hidden() * self.output()
-    }
-}
+/*
+    appellation: layout <module>
+    authors: @FL03
+*/
+
+/// The [`ModelLayout`] trait defines an interface for object capable of representing the
+/// _layout_; i.e. the number of input, hidden, and output features of a neural network model
+/// containing some number of hidden layers.
+pub trait ModelLayout: Copy + core::fmt::Debug {
+    /// returns a copy of the number of input features for the model
+    fn input(&self) -> usize;
+    /// returns a mutable reference to number of the input features for the model
+    fn input_mut(&mut self) -> &mut usize;
+    /// returns a copy of the number of hidden features for the model
+    fn hidden(&self) -> usize;
+    /// returns a mutable reference to the number of hidden features for the model
+    fn hidden_mut(&mut self) -> &mut usize;
+    /// returns a copy of the number of hidden layers for the model
+    fn layers(&self) -> usize;
+    /// returns a mutable reference to the number of hidden layers for the model
+    fn layers_mut(&mut self) -> &mut usize;
+    /// returns a copy of the output features for the model
+    fn output(&self) -> usize;
+    /// returns a mutable reference to the output features for the model
+    fn output_mut(&mut self) -> &mut usize;
+    #[inline]
+    /// update the number of input features for the model and return a mutable reference to the
+    /// current layout.
+    fn set_input(&mut self, input: usize) -> &mut Self {
+        *self.input_mut() = input;
+        self
+    }
+    #[inline]
+    /// update the number of hidden features for the model and return a mutable reference to
+    /// the current layout.
+    fn set_hidden(&mut self, hidden: usize) -> &mut Self {
+        *self.hidden_mut() = hidden;
+        self
+    }
+    #[inline]
+    /// update the number of hidden layers for the model and return a mutable reference to
+    /// the current layout.
+    fn set_layers(&mut self, layers: usize) -> &mut Self {
+        *self.layers_mut() = layers;
+        self
+    }
+    #[inline]
+    /// update the number of output features for the model and return a mutable reference to
+    /// the current layout.
+    fn set_output(&mut self, output: usize) -> &mut Self {
+        *self.output_mut() = output;
+        self
+    }
+    /// the dimension of the input layer; (input, hidden)
+    fn dim_input(&self) -> (usize, usize) {
+        (self.input(), self.hidden())
+    }
+    /// the dimension of the hidden layers; (hidden, hidden)
+    fn dim_hidden(&self) -> (usize, usize) {
+        (self.hidden(), self.hidden())
+    }
+    /// the dimension of the output layer; (hidden, output)
+    fn dim_output(&self) -> (usize, usize) {
+        (self.hidden(), self.output())
+    }
+    /// the total number of parameters in the model
+    fn size(&self) -> usize {
+        self.size_input() + self.size_hidden() + self.size_output()
+    }
+    /// the total number of input parameters in the model
+    fn size_input(&self) -> usize {
+        self.input() * self.hidden()
+    }
+    /// the total number of hidden parameters in the model
+    fn size_hidden(&self) -> usize {
+        self.hidden() * self.hidden() * self.layers()
+    }
+    /// the total number of output parameters in the model
+    fn size_output(&self) -> usize {
+        self.hidden() * self.output()
+    }
+}
diff --git a/neural/src/lib.rs b/neural/src/lib.rs
index 7a3ee8d4..b3170da2 100644
--- a/neural/src/lib.rs
+++ b/neural/src/lib.rs
@@ -1,134 +1,137 @@
-/*
-    Appellation: concision-neural <library>
-    Contrib: @FL03
-*/
-//! Various components, implementations, and traits for creating neural networks. The crate
-//! builds off of the [`concision_core`] crate, making extensive use of the [`ParamsBase`](cnc::ParamsBase)
-//! type to define the parameters of layers within a network.
-//!
-//! ## Overview
-//!
-//! Neural networks are a fundamental part of machine learning, and this crate provides a
-//! comprehensive set of tools to build, configure, and train neural network models. Listed
-//! below are several key components of the crate:
-//!
-//! - [`Model`]: A trait for defining a neural network model.
-//! - [`StandardModelConfig`]: A standard configuration for the models
-//! - [`ModelFeatures`]: A default implementation of the [`ModelLayout`] trait that
-//!   sufficiently defines both shallow and deep neural networks.
-//!
-//! ### _Model Parameters_
-//!
-//! Additionally, the crate defines a sequential
-//!
-//! **Note**: You should stick with the type aliases for the [`ModelParamsBase`] type, as they
-//! drastically simplify the type-face of the model parameters. Attempting to generalize over
-//! the hidden layers of the model might lead to excessive complexity. That being said, there
-//! are provided methods and routines to convert from a shallow to deep model, and vice versa.
-//!
-//! - [`DeepModelParams`]: An owned representation of the [`ModelParamsBase`] for deep
-//!   neural networks.
-//! - [`ShallowModelParams`]: An owned representation of the [`ModelParamsBase`] for shallow
-//!   neural networks.
-//!
-//! ### Traits
-//!
-//! This crate extends the [`Forward`](cnc::Forward) and [`Backward`](cnc::Backward) traits
-//! from the [`core`](cnc) crate to provide additional functionality for neural networks.
-//!
-//! - [`Predict`]: A more robust implementation of the [`Forward`] trait
-//! - [`Train`]: A trait for training a neural network model.
-//!
-#![cfg_attr(not(feature = "std"), no_std)]
-#![allow(
-    clippy::missing_saftey_doc,
-    clippy::module_inception,
-    clippy::needless_doctest_main,
-    clippy::upper_case_acronyms
-)]
-// ensure that either `std` or `alloc` feature is enabled
-#[cfg(not(any(feature = "std", feature = "alloc")))]
-compile_error! {
-    "At least one of the 'std' or 'alloc' features must be enabled."
-}
-
-extern crate concision_core as cnc;
-
-#[cfg(feature = "alloc")]
-extern crate alloc;
-
-#[doc(inline)]
-pub use self::{
-    config::prelude::*,
-    error::*,
-    layers::{Layer, LayerBase},
-    layout::prelude::*,
-    params::prelude::*,
-    train::prelude::*,
-    traits::*,
-    types::*,
-};
-
-#[macro_use]
-pub(crate) mod macros {
-    #[macro_use]
-    pub mod seal;
-}
-
-pub mod config;
-pub mod error;
-pub mod layers;
-pub mod layout;
-pub mod params;
-pub mod train;
-
-pub(crate) mod traits {
-    #[doc(inline)]
-    pub use self::prelude::*;
-
-    mod hidden;
-    mod models;
-    mod predict;
-
-    mod prelude {
-        #[doc(inline)]
-        pub use super::hidden::*;
-        #[doc(inline)]
-        pub use super::models::*;
-        #[doc(inline)]
-        pub use super::predict::*;
-    }
-}
-
-pub(crate) mod types {
-    #[doc(inline)]
-    pub use self::prelude::*;
-
-    mod dropout;
-    mod key_value;
-
-    mod prelude {
-        #[doc(inline)]
-        pub use super::dropout::*;
-        #[doc(inline)]
-        pub use super::key_value::*;
-    }
-}
-
-#[doc(hidden)]
-pub mod prelude {
-    #[doc(no_inline)]
-    pub use super::config::prelude::*;
-    #[doc(hidden)]
-    pub use crate::layers::prelude::*;
-    #[doc(no_inline)]
-    pub use crate::layout::prelude::*;
-    #[doc(no_inline)]
-    pub use crate::params::prelude::*;
-    #[doc(no_inline)]
-    pub use crate::train::prelude::*;
-    #[doc(no_inline)]
-    pub use crate::traits::*;
-    #[doc(no_inline)]
-    pub use crate::types::*;
-}
+/*
+    Appellation: concision-neural <library>
+    Contrib: @FL03
+*/
+//! Various components, implementations, and traits for creating neural networks. The crate
+//! builds off of the [`concision_core`] crate, making extensive use of the [`ParamsBase`](cnc::ParamsBase)
+//! type to define the parameters of layers within a network.
+//!
+//! ## Overview
+//!
+//! Neural networks are a fundamental part of machine learning, and this crate provides a
+//! comprehensive set of tools to build, configure, and train neural network models. Listed
+//! below are several key components of the crate:
+//!
+//! - [`Model`]: A trait for defining a neural network model.
+//! - [`StandardModelConfig`]: A standard configuration for the models
+//! - [`ModelFeatures`]: A default implementation of the [`ModelLayout`] trait that
+//!   sufficiently defines both shallow and deep neural networks.
+//!
+//! ### _Model Parameters_
+//!
+//! Additionally, the crate defines a sequential
+//!
+//! **Note**: You should stick with the type aliases for the [`ModelParamsBase`] type, as they
+//! drastically simplify the type-face of the model parameters. Attempting to generalize over
+//! the hidden layers of the model might lead to excessive complexity. That being said, there
+//! are provided methods and routines to convert from a shallow to deep model, and vice versa.
+//!
+//! - [`DeepModelParams`]: An owned representation of the [`ModelParamsBase`] for deep
+//!   neural networks.
+//! - [`ShallowModelParams`]: An owned representation of the [`ModelParamsBase`] for shallow
+//!   neural networks.
+//!
+//! ### Traits
+//!
+//! This crate extends the [`Forward`](cnc::Forward) and [`Backward`](cnc::Backward) traits
+//! from the [`core`](cnc) crate to provide additional functionality for neural networks.
+//!
+//! - [`Predict`]: A more robust implementation of the [`Forward`] trait
+//! - [`Train`]: A trait for training a neural network model.
+//!
+#![cfg_attr(not(feature = "std"), no_std)]
+#![allow(
+    clippy::missing_saftey_doc,
+    clippy::module_inception,
+    clippy::needless_doctest_main,
+    clippy::upper_case_acronyms
+)]
+// ensure that either `std` or `alloc` feature is enabled
+#[cfg(not(any(feature = "std", feature = "alloc")))]
+compile_error! {
+    "At least one of the 'std' or 'alloc' features must be enabled."
+}
+
+extern crate concision_core as cnc;
+
+#[cfg(feature = "alloc")]
+extern crate alloc;
+
+#[doc(inline)]
+pub use self::{
+    config::prelude::*,
+    error::*,
+    layers::{Layer, LayerBase},
+    layout::prelude::*,
+    params::prelude::*,
+    train::prelude::*,
+    traits::*,
+    types::*,
+};
+
+#[macro_use]
+pub(crate) mod macros {
+    #[macro_use]
+    pub mod seal;
+}
+
+pub mod config;
+pub mod error;
+pub mod layers;
+pub mod layout;
+pub mod params;
+pub mod train;
+
+pub(crate) mod traits {
+    #[doc(inline)]
+    pub use self::prelude::*;
+
+    mod hidden;
+    mod models;
+    mod network;
+    mod predict;
+
+    mod prelude {
+        #[doc(inline)]
+        pub use super::hidden::*;
+        #[doc(inline)]
+        pub use super::models::*;
+        #[doc(inline)]
+        pub use super::network::*;
+        #[doc(inline)]
+        pub use super::predict::*;
+    }
+}
+
+pub(crate) mod types {
+    #[doc(inline)]
+    pub use self::prelude::*;
+
+    mod dropout;
+    mod key_value;
+
+    mod prelude {
+        #[doc(inline)]
+        pub use super::dropout::*;
+        #[doc(inline)]
+        pub use super::key_value::*;
+    }
+}
+
+#[doc(hidden)]
+pub mod prelude {
+    #[doc(no_inline)]
+    pub use super::config::prelude::*;
+    #[doc(hidden)]
+    pub use crate::layers::prelude::*;
+    #[doc(no_inline)]
+    pub use crate::layout::prelude::*;
+    #[doc(no_inline)]
+    pub use crate::params::prelude::*;
+    #[doc(no_inline)]
+    pub use crate::train::prelude::*;
+    #[doc(no_inline)]
+    pub use crate::traits::*;
+    #[doc(no_inline)]
+    pub use crate::types::*;
+}
diff --git a/neural/src/params/impls/impl_model_params.rs b/neural/src/params/impls/impl_model_params.rs
index 84b5f964..8347bf3e 100644
--- a/neural/src/params/impls/impl_model_params.rs
+++ b/neural/src/params/impls/impl_model_params.rs
@@ -8,7 +8,7 @@ use crate::{DeepModelRepr, RawHidden};
 use cnc::params::ParamsBase;
 use ndarray::{Data, Dimension, RawDataClone};
 
-impl<A, S, D, H> Clone for ModelParamsBase<S, D, H>
+impl<A, S, D, H> Clone for ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     H: RawHidden<S, D> + Clone,
@@ -24,7 +24,7 @@ where
     }
 }
 
-impl<A, S, D, H> core::fmt::Debug for ModelParamsBase<S, D, H>
+impl<A, S, D, H> core::fmt::Debug for ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     H: RawHidden<S, D> + core::fmt::Debug,
@@ -40,7 +40,7 @@ where
     }
 }
 
-impl<A, S, D, H> core::fmt::Display for ModelParamsBase<S, D, H>
+impl<A, S, D, H> core::fmt::Display for ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     H: RawHidden<S, D> + core::fmt::Debug,
@@ -58,7 +58,7 @@ where
     }
 }
 
-impl<A, S, D, H> core::ops::Index<usize> for ModelParamsBase<S, D, H>
+impl<A, S, D, H> core::ops::Index<usize> for ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
@@ -78,7 +78,7 @@ where
     }
 }
 
-impl<A, S, D, H> core::ops::IndexMut<usize> for ModelParamsBase<S, D, H>
+impl<A, S, D, H> core::ops::IndexMut<usize> for ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
diff --git a/neural/src/params/impls/impl_model_params_rand.rs b/neural/src/params/impls/impl_model_params_rand.rs
index a533e058..ca9fe26d 100644
--- a/neural/src/params/impls/impl_model_params_rand.rs
+++ b/neural/src/params/impls/impl_model_params_rand.rs
@@ -14,7 +14,7 @@ use num_traits::{Float, FromPrimitive};
 use rand_distr::uniform::{SampleUniform, Uniform};
 use rand_distr::{Distribution, StandardNormal};
 
-impl<A, S> ShallowParamsBase<S, Ix2>
+impl<A, S> ShallowParamsBase<S, Ix2, A>
 where
     S: DataOwned<Elem = A>,
 {
@@ -74,7 +74,7 @@ where
     }
 }
 
-impl<A, S> DeepParamsBase<S, Ix2>
+impl<A, S> DeepParamsBase<S, Ix2, A>
 where
     S: DataOwned<Elem = A>,
 {
diff --git a/neural/src/params/impls/impl_model_params_serde.rs b/neural/src/params/impls/impl_model_params_serde.rs
index 0eefa3e0..345271a4 100644
--- a/neural/src/params/impls/impl_model_params_serde.rs
+++ b/neural/src/params/impls/impl_model_params_serde.rs
@@ -14,16 +14,16 @@ use serde::ser::{Serialize, SerializeStruct, Serializer};
 /// serialization and deserialization.
 const FIELDS: [&str; 3] = ["input", "hidden", "output"];
 
-struct ModelParamsBaseVisitor<S, D, H>
+struct ModelParamsBaseVisitor<S, D, H, A = <S as RawData>::Elem>
 where
     D: Dimension,
-    S: RawData,
+    S: RawData<Elem = A>,
     H: RawHidden<S, D>,
 {
-    marker: PhantomData<(S, D, H)>,
+    marker: PhantomData<(S, D, H, A)>,
 }
 
-impl<'a, A, S, D, H> Visitor<'a> for ModelParamsBaseVisitor<S, D, H>
+impl<'a, A, S, D, H> Visitor<'a> for ModelParamsBaseVisitor<S, D, H, A>
 where
     A: Deserialize<'a>,
     D: Dimension + Deserialize<'a>,
@@ -31,7 +31,7 @@ where
     H: RawHidden<S, D> + Deserialize<'a>,
     <D as Dimension>::Smaller: Deserialize<'a>,
 {
-    type Value = ModelParamsBase<S, D, H>;
+    type Value = ModelParamsBase<S, D, H, A>;
 
     fn expecting(&self, formatter: &mut std::fmt::Formatter) -> std::fmt::Result {
         formatter.write_str("The visitor is expecting to receive a `ModelParamsBase` object.")
@@ -59,7 +59,7 @@ where
     }
 }
 
-impl<'a, A, S, D, H> Deserialize<'a> for ModelParamsBase<S, D, H>
+impl<'a, A, S, D, H> Deserialize<'a> for ModelParamsBase<S, D, H, A>
 where
     A: Deserialize<'a>,
     D: Dimension + Deserialize<'a>,
@@ -81,7 +81,7 @@ where
     }
 }
 
-impl<A, S, D, H> Serialize for ModelParamsBase<S, D, H>
+impl<A, S, D, H> Serialize for ModelParamsBase<S, D, H, A>
 where
     A: Serialize,
     D: Dimension + Serialize,
diff --git a/neural/src/params/impls/impl_params_deep.rs b/neural/src/params/impls/impl_params_deep.rs
index cc0acd4c..920720f5 100644
--- a/neural/src/params/impls/impl_params_deep.rs
+++ b/neural/src/params/impls/impl_params_deep.rs
@@ -6,11 +6,11 @@ use crate::{DeepParamsBase, ModelParamsBase};
 
 use crate::ModelFeatures;
 use crate::traits::DeepModelRepr;
-use cnc::params::ParamsBase;
+use concision_params::ParamsBase;
 use ndarray::{Data, DataOwned, Dimension, Ix2, RawData};
 use num_traits::{One, Zero};
 
-impl<S, D, H, A> ModelParamsBase<S, D, H>
+impl<S, D, H, A> ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
@@ -26,7 +26,7 @@ where
     }
 }
 
-impl<A, S, D> DeepParamsBase<S, D>
+impl<A, S, D> DeepParamsBase<S, D, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
@@ -101,7 +101,7 @@ where
     /// sequentially forwards the input through the model without any activations or other
     /// complexities in-between. not overly usefuly, but it is here for completeness
     #[inline]
-    pub fn forward<X, Y>(&self, input: &X) -> cnc::Result<Y>
+    pub fn forward<X, Y>(&self, input: &X) -> Option<Y>
     where
         A: Clone,
         S: Data,
@@ -118,7 +118,7 @@ where
     }
 }
 
-impl<A, S> DeepParamsBase<S, Ix2>
+impl<A, S> DeepParamsBase<S, Ix2, A>
 where
     S: RawData<Elem = A>,
 {
diff --git a/neural/src/params/impls/impl_params_shallow.rs b/neural/src/params/impls/impl_params_shallow.rs
index 81529bd6..06cb1bf9 100644
--- a/neural/src/params/impls/impl_params_shallow.rs
+++ b/neural/src/params/impls/impl_params_shallow.rs
@@ -6,13 +6,14 @@ use crate::params::{ModelParamsBase, ShallowParamsBase};
 
 use crate::ModelFeatures;
 use crate::traits::ShallowModelRepr;
-use cnc::{ParamsBase, ReLU, Sigmoid};
+use cnc::{ReLU, Sigmoid};
+use concision_params::ParamsBase;
 use ndarray::{
     Array1, ArrayBase, Data, DataOwned, Dimension, Ix2, RawData, RemoveAxis, ScalarOperand,
 };
 use num_traits::Float;
 
-impl<S, D, H, A> ModelParamsBase<S, D, H>
+impl<S, D, H, A> ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
@@ -28,7 +29,7 @@ where
     }
 }
 
-impl<S, D, A> ShallowParamsBase<S, D>
+impl<S, D, A> ShallowParamsBase<S, D, A>
 where
     S: RawData<Elem = A>,
     D: Dimension,
@@ -56,16 +57,16 @@ where
         size + self.output().count_weight()
     }
     /// returns an immutable reference to the hidden weights
-    pub const fn hidden_weights(&self) -> &ArrayBase<S, D> {
+    pub const fn hidden_weights(&self) -> &ArrayBase<S, D, A> {
         self.hidden().weights()
     }
     /// returns an mutable reference to the hidden weights
-    pub const fn hidden_weights_mut(&mut self) -> &mut ArrayBase<S, D> {
+    pub const fn hidden_weights_mut(&mut self) -> &mut ArrayBase<S, D, A> {
         self.hidden_mut().weights_mut()
     }
 }
 
-impl<S, A> ShallowParamsBase<S, Ix2>
+impl<S, A> ShallowParamsBase<S, Ix2, A>
 where
     S: RawData<Elem = A>,
 {
@@ -81,7 +82,7 @@ where
         }
     }
     /// forward input through the controller network
-    pub fn forward(&self, input: &Array1<A>) -> cnc::Result<Array1<A>>
+    pub fn forward(&self, input: &Array1<A>) -> Option<Array1<A>>
     where
         A: Float + ScalarOperand,
         S: Data,
@@ -93,11 +94,11 @@ where
         // forward the input through the output layer; activate using sigmoid
         output = self.output().forward(&output)?.sigmoid();
 
-        Ok(output)
+        Some(output)
     }
 }
 
-impl<A, S> Default for ShallowParamsBase<S, Ix2>
+impl<A, S> Default for ShallowParamsBase<S, Ix2, A>
 where
     S: DataOwned<Elem = A>,
     A: Clone + Default,
diff --git a/neural/src/params/model_params.rs b/neural/src/params/model_params.rs
index bf6cfa68..641cd60c 100644
--- a/neural/src/params/model_params.rs
+++ b/neural/src/params/model_params.rs
@@ -21,10 +21,10 @@ use crate::{DeepModelRepr, RawHidden};
 ///
 /// This type also enables us to define a set of common initialization routines and introduce
 /// other standards for dealing with parameters in a neural network.
-pub struct ModelParamsBase<S, D, H>
+pub struct ModelParamsBase<S, D, H, A = <S as RawData>::Elem>
 where
     D: Dimension,
-    S: RawData,
+    S: RawData<Elem = A>,
     H: RawHidden<S, D>,
 {
     /// the input layer of the model
@@ -38,7 +38,7 @@ where
 /// storage type `S`, the dimension `D`, and the hidden layer type `H`. This implementation
 /// focuses on providing basic initialization routines and accessors for the various layers
 /// within the model.
-impl<S, D, H, A> ModelParamsBase<S, D, H>
+impl<S, D, H, A> ModelParamsBase<S, D, H, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
@@ -119,35 +119,35 @@ where
         self.hidden().as_slice()
     }
     /// returns an immutable reference to the input bias
-    pub const fn input_bias(&self) -> &ArrayBase<S, D::Smaller> {
+    pub const fn input_bias(&self) -> &ArrayBase<S, D::Smaller, A> {
         self.input().bias()
     }
     /// returns a mutable reference to the input bias
-    pub const fn input_bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller> {
+    pub const fn input_bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller, A> {
         self.input_mut().bias_mut()
     }
     /// returns an immutable reference to the input weights
-    pub const fn input_weights(&self) -> &ArrayBase<S, D> {
+    pub const fn input_weights(&self) -> &ArrayBase<S, D, A> {
         self.input().weights()
     }
     /// returns an mutable reference to the input weights
-    pub const fn input_weights_mut(&mut self) -> &mut ArrayBase<S, D> {
+    pub const fn input_weights_mut(&mut self) -> &mut ArrayBase<S, D, A> {
         self.input_mut().weights_mut()
     }
     /// returns an immutable reference to the output bias
-    pub const fn output_bias(&self) -> &ArrayBase<S, D::Smaller> {
+    pub const fn output_bias(&self) -> &ArrayBase<S, D::Smaller, A> {
         self.output().bias()
     }
     /// returns a mutable reference to the output bias
-    pub const fn output_bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller> {
+    pub const fn output_bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller, A> {
         self.output_mut().bias_mut()
     }
     /// returns an immutable reference to the output weights
-    pub const fn output_weights(&self) -> &ArrayBase<S, D> {
+    pub const fn output_weights(&self) -> &ArrayBase<S, D, A> {
         self.output().weights()
     }
     /// returns an mutable reference to the output weights
-    pub const fn output_weights_mut(&mut self) -> &mut ArrayBase<S, D> {
+    pub const fn output_weights_mut(&mut self) -> &mut ArrayBase<S, D, A> {
         self.output_mut().weights_mut()
     }
     /// returns the number of hidden layers in the model
diff --git a/neural/src/params/types/aliases.rs b/neural/src/params/types/aliases.rs
index dc38f2f7..94910628 100644
--- a/neural/src/params/types/aliases.rs
+++ b/neural/src/params/types/aliases.rs
@@ -8,17 +8,17 @@ use ndarray::{Ix2, OwnedRepr};
 
 /// A type alias for an owned representation of the [`ModelParamsBase`] generic of type `A`
 /// and the dimension `D`.
-pub type ModelParams<A, D, H> = ModelParamsBase<OwnedRepr<A>, D, H>;
+pub type ModelParams<A, D, H> = ModelParamsBase<OwnedRepr<A>, D, H, A>;
 /// a type alias for an owned representation of the [`DeepParamsBase`] generic of type `A` and
 /// the dimension `D`.
-pub type DeepModelParams<A, D = Ix2> = DeepParamsBase<OwnedRepr<A>, D>;
+pub type DeepModelParams<A, D = Ix2> = DeepParamsBase<OwnedRepr<A>, D, A>;
 /// a type alias for a _deep_ representation of the [`ModelParamsBase`] using a vector of
 /// parameters as the hidden layers.
-pub type DeepParamsBase<S, D> = ModelParamsBase<S, D, Vec<ParamsBase<S, D>>>;
+pub type DeepParamsBase<S, D, A = f32> = ModelParamsBase<S, D, Vec<ParamsBase<S, D, A>>, A>;
 
 /// a type alias for an owned representation of the [`DeepParamsBase`] generic of type `A` and
 /// the dimension `D`.
 pub type ShallowModelParams<A, D = Ix2> = ShallowParamsBase<OwnedRepr<A>, D>;
 /// a type alias for a _shallow_ representation of the [`ModelParamsBase`] using a single
 /// [`ParamsBase`] instance as the hidden layer.
-pub type ShallowParamsBase<S, D> = ModelParamsBase<S, D, ParamsBase<S, D>>;
+pub type ShallowParamsBase<S, D, A = f32> = ModelParamsBase<S, D, ParamsBase<S, D, A>, A>;
diff --git a/neural/src/train/error.rs b/neural/src/train/error.rs
index ed5a0441..08c6ba27 100644
--- a/neural/src/train/error.rs
+++ b/neural/src/train/error.rs
@@ -5,7 +5,7 @@ pub(crate) type TrainingResult<T> = Result<T, TrainingError>;
 
 /// The [`TrainingError`] type enumerates the various errors that can occur during the
 /// training process.
-#[derive(Debug, scsys::VariantConstructors, thiserror::Error)]
+#[derive(Debug, thiserror::Error, variants::VariantConstructors)]
 #[non_exhaustive]
 pub enum TrainingError {
     #[error("Invalid Training Data")]
diff --git a/neural/src/train/traits/train.rs b/neural/src/train/traits/train.rs
index 0bb9d6e8..c7a5e58e 100644
--- a/neural/src/train/traits/train.rs
+++ b/neural/src/train/traits/train.rs
@@ -4,15 +4,15 @@
 */
 use crate::train::error::TrainingError;
 
-use crate::error::ModelResult;
+use crate::error::NeuralResult;
 
 /// This trait defines the training process for the network
 pub trait Train<X, Y> {
     type Output;
 
-    fn train(&mut self, input: &X, target: &Y) -> ModelResult<Self::Output>;
+    fn train(&mut self, input: &X, target: &Y) -> NeuralResult<Self::Output>;
 
-    fn train_for(&mut self, input: &X, target: &Y, epochs: usize) -> ModelResult<Self::Output> {
+    fn train_for(&mut self, input: &X, target: &Y, epochs: usize) -> NeuralResult<Self::Output> {
         let mut output = None;
 
         for _ in 0..epochs {
diff --git a/neural/src/traits/models.rs b/neural/src/traits/models.rs
index cc742057..1e98487f 100644
--- a/neural/src/traits/models.rs
+++ b/neural/src/traits/models.rs
@@ -1,150 +1,146 @@
-/*
-    appellation: models <module>
-    authors: @FL03
-*/
-use crate::config::NetworkConfig;
-use crate::{DeepModelParams, ModelLayout};
-use crate::{Predict, Train};
-use concision_core::params::Params;
-use concision_data::DatasetBase;
-
-/// The [`Model`] trait defines the core interface for all models; implementors will need to
-/// provide the type of configuration used by the model, the type of layout used by the model,
-/// and the type of parameters used by the model. The crate provides standard, or default,
-/// definitions of both the configuration and layout types, however, for
-pub trait Model<T = f32> {
-    /// The type of configuration used for the model
-    type Config: NetworkConfig<T>;
-    /// The type of [`ModelLayout`] used by the model for this implementation.
-    type Layout: ModelLayout;
-    /// returns an immutable reference to the models configuration; this is typically used to
-    /// access the models hyperparameters (i.e. learning rate, momentum, etc.) and other
-    /// related control parameters.
-    fn config(&self) -> &Self::Config;
-    /// returns a mutable reference to the models configuration; useful for setting hyperparams
-    fn config_mut(&mut self) -> &mut Self::Config;
-    /// returns a copy of the model's current layout (features); a type providing the model
-    /// with a particular number of features for the various layers of a deep neural network.
-    ///
-    /// the layout is used in everything from creation and initialization routines to
-    /// validating the dimensionality of the model's inputs, outputs, training data, etc.
-    fn layout(&self) -> Self::Layout;
-    /// returns an immutable reference to the model parameters
-    fn params(&self) -> &DeepModelParams<T>;
-    /// returns a mutable reference to the model's parameters
-    fn params_mut(&mut self) -> &mut DeepModelParams<T>;
-    /// propagates the input through the model; each layer is applied in sequence meaning that
-    /// the output of each previous layer is the input to the next layer. This pattern
-    /// repeats until the output layer returns the final result.
-    ///
-    /// By default, the trait simply passes each output from one layer to the next, however,
-    /// custom models will likely override this method to inject activation methods and other
-    /// related logic
-    fn predict<U, V>(&self, inputs: &U) -> crate::ModelResult<V>
-    where
-        Self: Predict<U, Output = V>,
-    {
-        Predict::predict(self, inputs)
-    }
-    /// a convience method that trains the model using the provided dataset; this method
-    /// requires that the model implements the [`Train`] trait and that the dataset
-    fn train<U, V, W>(&mut self, dataset: &DatasetBase<U, V>) -> crate::ModelResult<W>
-    where
-        Self: Train<U, V, Output = W>,
-    {
-        Train::train(self, dataset.records(), dataset.targets())
-    }
-}
-
-pub trait ModelExt<T>: Model<T> {
-    /// [`replace`](core::mem::replace) the current configuration and returns the old one;
-    fn replace_config(&mut self, config: Self::Config) -> Self::Config {
-        core::mem::replace(self.config_mut(), config)
-    }
-    /// [`replace`](core::mem::replace) the current model parameters and returns the old one
-    fn replace_params(&mut self, params: DeepModelParams<T>) -> DeepModelParams<T> {
-        core::mem::replace(self.params_mut(), params)
-    }
-    /// overrides the current configuration and returns a mutable reference to the model
-    fn set_config(&mut self, config: Self::Config) -> &mut Self {
-        *self.config_mut() = config;
-        self
-    }
-    /// overrides the current model parameters and returns a mutable reference to the model
-    fn set_params(&mut self, params: DeepModelParams<T>) -> &mut Self {
-        *self.params_mut() = params;
-        self
-    }
-    /// returns an immutable reference to the input layer;
-    #[inline]
-    fn input_layer(&self) -> &Params<T> {
-        self.params().input()
-    }
-    /// returns a mutable reference to the input layer;
-    #[inline]
-    fn input_layer_mut(&mut self) -> &mut Params<T> {
-        self.params_mut().input_mut()
-    }
-    /// returns an immutable reference to the hidden layer(s);
-    #[inline]
-    fn hidden_layers(&self) -> &Vec<Params<T>> {
-        self.params().hidden()
-    }
-    /// returns a mutable reference to the hidden layer(s);
-    #[inline]
-    fn hidden_layers_mut(&mut self) -> &mut Vec<Params<T>> {
-        self.params_mut().hidden_mut()
-    }
-    /// returns an immutable reference to the output layer;
-    #[inline]
-    fn output_layer(&self) -> &Params<T> {
-        self.params().output()
-    }
-    /// returns a mutable reference to the output layer;
-    #[inline]
-    fn output_layer_mut(&mut self) -> &mut Params<T> {
-        self.params_mut().output_mut()
-    }
-    #[inline]
-    fn set_input_layer(&mut self, layer: Params<T>) -> &mut Self {
-        self.params_mut().set_input(layer);
-        self
-    }
-    #[inline]
-    fn set_hidden_layers(&mut self, layers: Vec<Params<T>>) -> &mut Self {
-        self.params_mut().set_hidden(layers);
-        self
-    }
-    #[inline]
-    fn set_output_layer(&mut self, layer: Params<T>) -> &mut Self {
-        self.params_mut().set_output(layer);
-        self
-    }
-    /// returns a 2-tuple representing the dimensions of the input layer; (input, hidden)
-    fn input_dim(&self) -> (usize, usize) {
-        self.layout().dim_input()
-    }
-    /// returns a 2-tuple representing the dimensions of the hidden layers; (hidden, hidden)
-    fn hidden_dim(&self) -> (usize, usize) {
-        self.layout().dim_hidden()
-    }
-    /// returns the total number of hidden layers in the model;
-    fn hidden_layers_count(&self) -> usize {
-        self.layout().layers()
-    }
-    /// returns a 2-tuple representing the dimensions of the output layer; (hidden, output)
-    fn output_dim(&self) -> (usize, usize) {
-        self.layout().dim_output()
-    }
-}
-
-/// The [`DeepNeuralNetwork`] trait is a specialization of the [`Model`] trait that
-/// provides additional functionality for deep neural networks. This trait is
-pub trait DeepNeuralNetwork<T = f32>: Model<T> {}
-
-impl<M, T> ModelExt<T> for M
-where
-    M: Model<T>,
-    M::Layout: ModelLayout,
-{
-}
+/*
+    appellation: models <module>
+    authors: @FL03
+*/
+use crate::config::NetworkConfig;
+use crate::{DeepModelParams, ModelLayout};
+use crate::{Predict, Train};
+use concision_core::params::Params;
+use concision_data::DatasetBase;
+
+/// The [`Model`] trait defines the core interface for all models; implementors will need to
+/// provide the type of configuration used by the model, the type of layout used by the model,
+/// and the type of parameters used by the model. The crate provides standard, or default,
+/// definitions of both the configuration and layout types, however, for
+pub trait Model<T = f32> {
+    /// The type of configuration used for the model
+    type Config: NetworkConfig<T>;
+    /// The type of [`ModelLayout`] used by the model for this implementation.
+    type Layout: ModelLayout;
+    /// returns an immutable reference to the models configuration; this is typically used to
+    /// access the models hyperparameters (i.e. learning rate, momentum, etc.) and other
+    /// related control parameters.
+    fn config(&self) -> &Self::Config;
+    /// returns a mutable reference to the models configuration; useful for setting hyperparams
+    fn config_mut(&mut self) -> &mut Self::Config;
+    /// returns a copy of the model's current layout (features); a type providing the model
+    /// with a particular number of features for the various layers of a deep neural network.
+    ///
+    /// the layout is used in everything from creation and initialization routines to
+    /// validating the dimensionality of the model's inputs, outputs, training data, etc.
+    fn layout(&self) -> Self::Layout;
+    /// returns an immutable reference to the model parameters
+    fn params(&self) -> &DeepModelParams<T>;
+    /// returns a mutable reference to the model's parameters
+    fn params_mut(&mut self) -> &mut DeepModelParams<T>;
+    /// propagates the input through the model; each layer is applied in sequence meaning that
+    /// the output of each previous layer is the input to the next layer. This pattern
+    /// repeats until the output layer returns the final result.
+    ///
+    /// By default, the trait simply passes each output from one layer to the next, however,
+    /// custom models will likely override this method to inject activation methods and other
+    /// related logic
+    fn predict<U, V>(&self, inputs: &U) -> Option<V>
+    where
+        Self: Predict<U, Output = V>,
+    {
+        Predict::predict(self, inputs)
+    }
+    /// a convience method that trains the model using the provided dataset; this method
+    /// requires that the model implements the [`Train`] trait and that the dataset
+    fn train<U, V, W>(&mut self, dataset: &DatasetBase<U, V>) -> crate::NeuralResult<W>
+    where
+        Self: Train<U, V, Output = W>,
+    {
+        Train::train(self, dataset.records(), dataset.targets())
+    }
+}
+
+pub trait ModelExt<T>: Model<T> {
+    /// [`replace`](core::mem::replace) the current configuration and returns the old one;
+    fn replace_config(&mut self, config: Self::Config) -> Self::Config {
+        core::mem::replace(self.config_mut(), config)
+    }
+    /// [`replace`](core::mem::replace) the current model parameters and returns the old one
+    fn replace_params(&mut self, params: DeepModelParams<T>) -> DeepModelParams<T> {
+        core::mem::replace(self.params_mut(), params)
+    }
+    /// overrides the current configuration and returns a mutable reference to the model
+    fn set_config(&mut self, config: Self::Config) -> &mut Self {
+        *self.config_mut() = config;
+        self
+    }
+    /// overrides the current model parameters and returns a mutable reference to the model
+    fn set_params(&mut self, params: DeepModelParams<T>) -> &mut Self {
+        *self.params_mut() = params;
+        self
+    }
+    /// returns an immutable reference to the input layer;
+    #[inline]
+    fn input_layer(&self) -> &Params<T> {
+        self.params().input()
+    }
+    /// returns a mutable reference to the input layer;
+    #[inline]
+    fn input_layer_mut(&mut self) -> &mut Params<T> {
+        self.params_mut().input_mut()
+    }
+    /// returns an immutable reference to the hidden layer(s);
+    #[inline]
+    fn hidden_layers(&self) -> &Vec<Params<T>> {
+        self.params().hidden()
+    }
+    /// returns a mutable reference to the hidden layer(s);
+    #[inline]
+    fn hidden_layers_mut(&mut self) -> &mut Vec<Params<T>> {
+        self.params_mut().hidden_mut()
+    }
+    /// returns an immutable reference to the output layer;
+    #[inline]
+    fn output_layer(&self) -> &Params<T> {
+        self.params().output()
+    }
+    /// returns a mutable reference to the output layer;
+    #[inline]
+    fn output_layer_mut(&mut self) -> &mut Params<T> {
+        self.params_mut().output_mut()
+    }
+    #[inline]
+    fn set_input_layer(&mut self, layer: Params<T>) -> &mut Self {
+        self.params_mut().set_input(layer);
+        self
+    }
+    #[inline]
+    fn set_hidden_layers(&mut self, layers: Vec<Params<T>>) -> &mut Self {
+        self.params_mut().set_hidden(layers);
+        self
+    }
+    #[inline]
+    fn set_output_layer(&mut self, layer: Params<T>) -> &mut Self {
+        self.params_mut().set_output(layer);
+        self
+    }
+    /// returns a 2-tuple representing the dimensions of the input layer; (input, hidden)
+    fn input_dim(&self) -> (usize, usize) {
+        self.layout().dim_input()
+    }
+    /// returns a 2-tuple representing the dimensions of the hidden layers; (hidden, hidden)
+    fn hidden_dim(&self) -> (usize, usize) {
+        self.layout().dim_hidden()
+    }
+    /// returns the total number of hidden layers in the model;
+    fn hidden_layers_count(&self) -> usize {
+        self.layout().layers()
+    }
+    /// returns a 2-tuple representing the dimensions of the output layer; (hidden, output)
+    fn output_dim(&self) -> (usize, usize) {
+        self.layout().dim_output()
+    }
+}
+
+impl<M, T> ModelExt<T> for M
+where
+    M: Model<T>,
+    M::Layout: ModelLayout,
+{
+}
diff --git a/neural/src/traits/network.rs b/neural/src/traits/network.rs
new file mode 100644
index 00000000..05aacb12
--- /dev/null
+++ b/neural/src/traits/network.rs
@@ -0,0 +1,35 @@
+/*
+    appellation: network <module>
+    authors: @FL03
+*/
+use super::{DeepModelRepr, RawHidden, ShallowModelRepr};
+use crate::config::NetworkConfig;
+use ndarray::{Dimension, RawData};
+
+pub trait NeuralNetwork<S, D>
+where
+    D: Dimension,
+    S: RawData,
+{
+    type Config: NetworkConfig<S::Elem>;
+    type Hidden: RawHidden<S, D>;
+
+    fn config(&self) -> &Self::Config;
+    fn config_mut(&mut self) -> &mut Self::Config;
+}
+
+pub trait ShallowNeuralNetwork<S, D>: NeuralNetwork<S, D>
+where
+    D: Dimension,
+    S: RawData,
+    Self::Hidden: ShallowModelRepr<S, D>,
+{
+}
+
+pub trait DeepNeuralNetwork<S, D>: NeuralNetwork<S, D>
+where
+    D: Dimension,
+    S: RawData,
+    Self::Hidden: DeepModelRepr<S, D>,
+{
+}
diff --git a/neural/src/traits/predict.rs b/neural/src/traits/predict.rs
index 57c265ca..bc5b814e 100644
--- a/neural/src/traits/predict.rs
+++ b/neural/src/traits/predict.rs
@@ -17,7 +17,7 @@ pub trait Predict<Rhs> {
 
     private!();
 
-    fn predict(&self, input: &Rhs) -> crate::ModelResult<Self::Output>;
+    fn predict(&self, input: &Rhs) -> Option<Self::Output>;
 }
 
 /// The [`PredictWithConfidence`] trait is an extension of the [`Predict`] trait, providing
@@ -25,10 +25,7 @@ pub trait Predict<Rhs> {
 pub trait PredictWithConfidence<Rhs>: Predict<Rhs> {
     type Confidence;
 
-    fn predict_with_confidence(
-        &self,
-        input: &Rhs,
-    ) -> crate::ModelResult<(Self::Output, Self::Confidence)>;
+    fn predict_with_confidence(&self, input: &Rhs) -> Option<(Self::Output, Self::Confidence)>;
 }
 
 /*
@@ -46,8 +43,8 @@ where
 
     seal!();
 
-    fn predict(&self, input: &U) -> crate::ModelResult<Self::Output> {
-        self.forward(input).map_err(core::convert::Into::into)
+    fn predict(&self, input: &U) -> Option<Self::Output> {
+        self.forward(input)
     }
 }
 
@@ -59,10 +56,7 @@ where
 {
     type Confidence = A;
 
-    fn predict_with_confidence(
-        &self,
-        input: &U,
-    ) -> Result<(Self::Output, Self::Confidence), crate::ModelError> {
+    fn predict_with_confidence(&self, input: &U) -> Option<(Self::Output, Self::Confidence)> {
         // Get the base prediction
         let prediction = Predict::predict(self, input)?;
         let shape = prediction.shape();
@@ -83,6 +77,6 @@ where
         // Confidence: inverse of variance (clipped to avoid division by zero)
         let confidence = (A::one() + avg_variance).recip();
 
-        Ok((prediction, confidence))
+        Some((prediction, confidence))
     }
 }
diff --git a/neural/src/types/dropout.rs b/neural/src/types/dropout.rs
index 2d848f6b..5fa915d2 100644
--- a/neural/src/types/dropout.rs
+++ b/neural/src/types/dropout.rs
@@ -39,7 +39,7 @@ where
 {
     type Output = <U as cnc::DropOut>::Output;
 
-    fn forward(&self, input: &U) -> cnc::Result<Self::Output> {
-        Ok(input.dropout(self.p))
+    fn forward(&self, input: &U) -> Option<Self::Output> {
+        Some(input.dropout(self.p))
     }
 }
diff --git a/neural/tests/layers.rs b/neural/tests/layers.rs
index 2fbb6262..42172f87 100644
--- a/neural/tests/layers.rs
+++ b/neural/tests/layers.rs
@@ -2,8 +2,8 @@
     appellation: layers <module>
     authors: @FL03
 */
-
+use concision_neural::NeuralResult;
 #[test]
-fn test_layer_base() -> anyhow::Result<()> {
+fn test_layer_base() -> NeuralResult<()> {
     Ok(())
 }
diff --git a/neural/tests/masks.rs b/neural/tests/masks.rs
index 1217d1ef..0780bed8 100644
--- a/neural/tests/masks.rs
+++ b/neural/tests/masks.rs
@@ -2,16 +2,16 @@ extern crate concision_core as cnc;
 extern crate concision_neural as neural;
 
 use cnc::Forward;
-use concision_neural::error::ModelError;
+use concision_neural::error::NeuralError;
 use ndarray::prelude::*;
 use neural::Dropout;
 
 #[test]
-fn test_dropout() -> Result<(), ModelError> {
+fn test_dropout() -> Result<(), NeuralError> {
     let shape = (512, 2048);
     let arr = Array2::<f64>::ones(shape);
     let dropout = Dropout::new(0.5);
-    let out = dropout.forward(&arr)?;
+    let out = dropout.forward(&arr).expect("Dropout forward pass failed");
 
     assert!(arr.iter().all(|&x| x == 1.0));
     assert!(out.iter().any(|x| x == &0f64));
diff --git a/params/Cargo.toml b/params/Cargo.toml
new file mode 100644
index 00000000..5538e3f9
--- /dev/null
+++ b/params/Cargo.toml
@@ -0,0 +1,180 @@
+[package]
+build = "build.rs"
+description = "this crate implements the core modules for the concision framework"
+name = "concision-params"
+
+authors.workspace = true
+categories.workspace = true
+edition.workspace = true
+homepage.workspace = true
+keywords.workspace = true
+license.workspace = true
+readme.workspace = true
+repository.workspace = true
+rust-version.workspace = true
+version.workspace = true
+
+[lib]
+crate-type = ["cdylib", "rlib"]
+bench = false
+doc = true
+doctest = true
+test = true
+
+# ************* [Unit Tests] *************
+[[test]]
+name = "default"
+
+[[test]]
+name = "params"
+required-features = ["std"]
+
+[dependencies]
+concision-init = { optional = true, workspace = true }
+concision-traits = { workspace = true }
+# custom
+variants = { workspace = true }
+# concurrency & parallelism
+rayon = { optional = true, workspace = true }
+# data & serialization
+serde = { features = ["derive"], optional = true, workspace = true }
+serde_derive = { optional = true, workspace = true }
+serde_json = { optional = true, workspace = true }
+# error-handling
+thiserror = { workspace = true }
+# mathematics
+approx = { optional = true, workspace = true }
+ndarray = { workspace = true }
+num-complex = { optional = true, workspace = true }
+num-traits = { workspace = true }
+# random
+getrandom = { default-features = false, optional = true, workspace = true }
+rand = { optional = true, workspace = true }
+rand_distr = { optional = true, workspace = true }
+
+[dev-dependencies]
+lazy_static = { workspace = true }
+
+[features]
+default = ["std"]
+
+full = [
+  "default",
+  "approx",
+  "complex",
+  "init",
+  "json",
+  "rand",
+  "serde",
+]
+
+nightly = [
+  "concision-init?/nightly",
+  "concision-traits/nightly",
+]
+
+# ************* [FF:Features] *************
+init = [
+  "concision_init",
+  "rand",
+]
+
+json = ["alloc", "serde", "serde_json"]
+
+concision_init = ["dep:concision-init"]
+
+# ************* [FF:Dependencies] *************
+std = [
+  "alloc",
+  "concision-init?/std",
+  "concision-traits/std",
+  "ndarray/std",
+  "num-complex?/std",
+  "num-traits/std",
+  "rand?/std",
+  "rand?/std_rng",
+  "serde/std",
+  "thiserror/std",
+  "variants/std",
+]
+
+wasi = [
+  "concision-init?/wasi",
+  "concision-traits/wasi",
+]
+
+wasm = [
+  "getrandom?/wasm_js",
+  "concision-init?/wasm",
+  "concision-traits/wasm",
+]
+# ************* [FF:Dependencies] *************
+alloc = [
+  "concision-init?/alloc",
+  "concision-traits/alloc",
+  "serde?/alloc",
+  "serde_json?/alloc",
+  "variants/alloc",
+]
+
+approx = [
+  "dep:approx",
+  "concision-init?/approx",
+  "ndarray/approx",
+]
+
+blas = [
+  "concision-init?/blas",
+  "ndarray/blas",
+]
+
+complex = [
+  "dep:num-complex",
+  "concision-init?/complex",
+]
+
+rand = [
+  "dep:rand",
+  "dep:rand_distr",
+  "concision-init?/rand",
+  "concision-traits/rand",
+  "num-complex?/rand",
+  "rng",
+]
+
+rayon = [
+  "dep:rayon",
+  "ndarray/rayon",
+]
+
+rng = [
+  "dep:getrandom",
+  "concision-init?/rng",
+  "concision-traits/rng",
+  "rand?/small_rng",
+  "rand?/thread_rng",
+]
+
+serde = [
+  "concision-init?/serde",
+  "dep:serde",
+  "dep:serde_derive",
+  "ndarray/serde",
+  "num-complex?/serde",
+  "rand?/serde",
+  "rand_distr?/serde",
+]
+
+serde_json = ["dep:serde_json"]
+
+
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
+
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
diff --git a/params/build.rs b/params/build.rs
new file mode 100644
index 00000000..940a4ce4
--- /dev/null
+++ b/params/build.rs
@@ -0,0 +1,8 @@
+/*
+    Appellation: build <build>
+    Contrib: FL03 <jo3mccain@icloud.com>
+*/
+
+fn main() {
+    println!("cargo::rustc-check-cfg=cfg(no_std)");
+}
diff --git a/core/src/params/error.rs b/params/src/error.rs
similarity index 69%
rename from core/src/params/error.rs
rename to params/src/error.rs
index eaa5a099..58547e6f 100644
--- a/core/src/params/error.rs
+++ b/params/src/error.rs
@@ -2,6 +2,11 @@
     Appellation: error <module>
     Contrib: @FL03
 */
+//! This module defines error types and handling mechanisms for the `params` crate.
+//!
+
+/// A type alias for a [`Result`](core::result::Result) which uses the [`ParamsError`] type
+pub type Result<T = ()> = core::result::Result<T, ParamsError>;
 
 /// the [`ParamsError`] enumerates various errors that can occur within the parameters of a
 /// neural network.
@@ -23,4 +28,6 @@ pub enum ParamsError {
     InvalidParameterType,
     #[error("Invalid parameter value")]
     InvalidParameterValue,
+    #[error(transparent)]
+    ShapeError(#[from] ndarray::ShapeError),
 }
diff --git a/core/src/params/impls/impl_params.rs b/params/src/impls/impl_params.rs
similarity index 79%
rename from core/src/params/impls/impl_params.rs
rename to params/src/impls/impl_params.rs
index 6d003d78..391028af 100644
--- a/core/src/params/impls/impl_params.rs
+++ b/params/src/impls/impl_params.rs
@@ -43,7 +43,7 @@ where
     }
 }
 
-impl<A, S, D> core::fmt::Debug for ParamsBase<S, D>
+impl<A, S, D> core::fmt::Debug for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
@@ -57,7 +57,7 @@ where
     }
 }
 
-impl<A, S, D> core::fmt::Display for ParamsBase<S, D>
+impl<A, S, D> core::fmt::Display for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
@@ -73,7 +73,7 @@ where
     }
 }
 
-impl<A, S, D> Clone for ParamsBase<S, D>
+impl<A, S, D> Clone for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: ndarray::RawDataClone<Elem = A>,
@@ -84,7 +84,7 @@ where
     }
 }
 
-impl<A, S, D> Copy for ParamsBase<S, D>
+impl<A, S, D> Copy for ParamsBase<S, D, A>
 where
     D: Dimension + Copy,
     <D as Dimension>::Smaller: Copy,
@@ -93,7 +93,7 @@ where
 {
 }
 
-impl<A, S, D> PartialEq for ParamsBase<S, D>
+impl<A, S, D> PartialEq for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
@@ -104,29 +104,29 @@ where
     }
 }
 
-impl<A, S, D> PartialEq<&ParamsBase<S, D>> for ParamsBase<S, D>
+impl<A, S, D> PartialEq<&ParamsBase<S, D, A>> for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
     A: PartialEq,
 {
-    fn eq(&self, other: &&ParamsBase<S, D>) -> bool {
+    fn eq(&self, other: &&ParamsBase<S, D, A>) -> bool {
         self.bias() == other.bias() && self.weights() == other.weights()
     }
 }
 
-impl<A, S, D> PartialEq<&mut ParamsBase<S, D>> for ParamsBase<S, D>
+impl<A, S, D> PartialEq<&mut ParamsBase<S, D, A>> for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
     A: PartialEq,
 {
-    fn eq(&self, other: &&mut ParamsBase<S, D>) -> bool {
+    fn eq(&self, other: &&mut ParamsBase<S, D, A>) -> bool {
         self.bias() == other.bias() && self.weights() == other.weights()
     }
 }
 
-impl<A, S, D> Eq for ParamsBase<S, D>
+impl<A, S, D> Eq for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: Data<Elem = A>,
@@ -134,13 +134,13 @@ where
 {
 }
 
-impl<A, S, D> IntoIterator for ParamsBase<S, D>
+impl<A, S, D> IntoIterator for ParamsBase<S, D, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
 {
-    type Item = ParamsBase<S, D>;
-    type IntoIter = Once<ParamsBase<S, D>>;
+    type Item = ParamsBase<S, D, A>;
+    type IntoIter = Once<ParamsBase<S, D, A>>;
 
     fn into_iter(self) -> Self::IntoIter {
         core::iter::once(self)
diff --git a/core/src/params/impls/impl_params_deprecated.rs b/params/src/impls/impl_params_deprecated.rs
similarity index 85%
rename from core/src/params/impls/impl_params_deprecated.rs
rename to params/src/impls/impl_params_deprecated.rs
index 0a5c19a3..4df62350 100644
--- a/core/src/params/impls/impl_params_deprecated.rs
+++ b/params/src/impls/impl_params_deprecated.rs
@@ -7,7 +7,7 @@ use crate::params::ParamsBase;
 use ndarray::{Dimension, RawData};
 
 #[doc(hidden)]
-impl<S, D, A> ParamsBase<S, D>
+impl<S, D, A> ParamsBase<S, D, A>
 where
     S: RawData<Elem = A>,
     D: Dimension,
diff --git a/core/src/params/impls/impl_params_init.rs b/params/src/impls/impl_params_init.rs
similarity index 93%
rename from core/src/params/impls/impl_params_init.rs
rename to params/src/impls/impl_params_init.rs
index 2e7ae370..063cda3c 100644
--- a/core/src/params/impls/impl_params_init.rs
+++ b/params/src/impls/impl_params_init.rs
@@ -4,7 +4,7 @@
 */
 use crate::params::ParamsBase;
 
-use crate::init::Initialize;
+use concision_init::Initialize;
 use ndarray::{
     ArrayBase, Axis, DataOwned, Dimension, RawData, RemoveAxis, ScalarOperand, ShapeBuilder,
 };
@@ -12,7 +12,7 @@ use num_traits::{Float, FromPrimitive};
 use rand::rngs::SmallRng;
 use rand_distr::Distribution;
 
-impl<A, S, D> ParamsBase<S, D>
+impl<A, S, D> ParamsBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
@@ -33,7 +33,7 @@ where
     }
 }
 
-impl<A, S, D> Initialize<S, D> for ParamsBase<S, D>
+impl<A, S, D> Initialize<S, D> for ParamsBase<S, D, A>
 where
     D: RemoveAxis,
     S: RawData<Elem = A>,
diff --git a/core/src/params/impls/impl_params_iter.rs b/params/src/impls/impl_params_iter.rs
similarity index 96%
rename from core/src/params/impls/impl_params_iter.rs
rename to params/src/impls/impl_params_iter.rs
index df2a6551..1531aba0 100644
--- a/core/src/params/impls/impl_params_iter.rs
+++ b/params/src/impls/impl_params_iter.rs
@@ -4,7 +4,7 @@
 */
 use crate::params::ParamsBase;
 
-use crate::params::iter::{Iter, IterMut};
+use crate::iter::{Iter, IterMut};
 use ndarray::iter as nditer;
 use ndarray::{Axis, Data, DataMut, Dimension, RawData, RemoveAxis};
 
@@ -14,7 +14,7 @@ use ndarray::{Axis, Data, DataMut, Dimension, RawData, RemoveAxis};
 /// - immutable and mutable iterators over each parameter (weights and bias) respectively;
 /// - an iterator over the parameters, which zips together an axis iterator over the columns of
 ///   the weights and an iterator over the bias;
-impl<S, D, A> ParamsBase<S, D>
+impl<S, D, A> ParamsBase<S, D, A>
 where
     S: RawData<Elem = A>,
     D: Dimension,
diff --git a/core/src/params/impls/impl_params_ops.rs b/params/src/impls/impl_params_ops.rs
similarity index 71%
rename from core/src/params/impls/impl_params_ops.rs
rename to params/src/impls/impl_params_ops.rs
index fbbbc5ab..bd06e02c 100644
--- a/core/src/params/impls/impl_params_ops.rs
+++ b/params/src/impls/impl_params_ops.rs
@@ -2,14 +2,38 @@
     Appellation: impl_ops <module>
     Contrib: @FL03
 */
-use crate::params::{Params, ParamsBase};
-use crate::{ApplyGradient, ApplyGradientExt, Backward, Forward, Norm};
+use crate::{Params, ParamsBase};
+use concision_traits::{
+    ApplyGradient, ApplyGradientExt, Backward, Biased, Forward, Norm, Weighted,
+};
 use ndarray::linalg::Dot;
-use ndarray::prelude::*;
 use ndarray::{ArrayBase, Data, DataMut, Dimension, ScalarOperand};
+use ndarray::{RawData, prelude::*};
 use num_traits::{Float, FromPrimitive};
 
-impl<A, S, D> ParamsBase<S, D>
+impl<A, S, D> ParamsBase<S, D, A>
+where
+    A: Clone,
+    D: Dimension,
+    S: Data<Elem = A>,
+{
+    /// perform a single backpropagation step
+    pub fn backward<X, Y, Z>(&mut self, input: &X, grad: &Y, lr: A) -> Option<Z>
+    where
+        Self: Backward<X, Y, Elem = A, Output = Z>,
+    {
+        <Self as Backward<X, Y>>::backward(self, input, grad, lr)
+    }
+    /// forward propagation
+    pub fn forward<X, Y>(&self, input: &X) -> Option<Y>
+    where
+        Self: Forward<X, Output = Y>,
+    {
+        <Self as Forward<X>>::forward(self, input)
+    }
+}
+
+impl<A, S, D> ParamsBase<S, D, A>
 where
     A: ScalarOperand + Float + FromPrimitive,
     D: Dimension,
@@ -27,9 +51,10 @@ where
         let weights = self.weights().l2_norm();
         bias + weights
     }
+
     /// a convenience method used to apply a gradient to the parameters using the given
     /// learning rate.
-    pub fn apply_gradient<Delta, Z>(&mut self, grad: &Delta, lr: A) -> crate::Result<Z>
+    pub fn apply_gradient<Delta, Z>(&mut self, grad: &Delta, lr: A) -> Option<Z>
     where
         S: DataMut,
         Self: ApplyGradient<Delta, A, Output = Z>,
@@ -37,12 +62,7 @@ where
         <Self as ApplyGradient<Delta, A>>::apply_gradient(self, grad, lr)
     }
 
-    pub fn apply_gradient_with_decay<Grad, Z>(
-        &mut self,
-        grad: &Grad,
-        lr: A,
-        decay: A,
-    ) -> crate::Result<Z>
+    pub fn apply_gradient_with_decay<Grad, Z>(&mut self, grad: &Grad, lr: A, decay: A) -> Option<Z>
     where
         S: DataMut,
         Self: ApplyGradient<Grad, A, Output = Z>,
@@ -56,7 +76,7 @@ where
         lr: A,
         momentum: A,
         velocity: &mut V,
-    ) -> crate::Result<Z>
+    ) -> Option<Z>
     where
         S: DataMut,
         Self: ApplyGradientExt<Grad, A, Output = Z, Velocity = V>,
@@ -73,7 +93,7 @@ where
         decay: A,
         momentum: A,
         velocity: &mut V,
-    ) -> crate::Result<Z>
+    ) -> Option<Z>
     where
         S: DataMut,
         Self: ApplyGradientExt<Grad, A, Output = Z, Velocity = V>,
@@ -84,7 +104,35 @@ where
     }
 }
 
-impl<A, S, T, D> ApplyGradient<ParamsBase<T, D>, A> for ParamsBase<S, D>
+impl<A, S, D> Weighted<S, D, A> for ParamsBase<S, D, A>
+where
+    S: RawData<Elem = A>,
+    D: Dimension,
+{
+    fn weights(&self) -> &ArrayBase<S, D, A> {
+        self.weights()
+    }
+
+    fn weights_mut(&mut self) -> &mut ArrayBase<S, D, A> {
+        self.weights_mut()
+    }
+}
+
+impl<A, S, D> Biased<S, D, A> for ParamsBase<S, D, A>
+where
+    S: RawData<Elem = A>,
+    D: Dimension,
+{
+    fn bias(&self) -> &ArrayBase<S, D::Smaller, A> {
+        self.bias()
+    }
+
+    fn bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller, A> {
+        self.bias_mut()
+    }
+}
+
+impl<A, S, T, D> ApplyGradient<ParamsBase<T, D>, A> for ParamsBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: DataMut<Elem = A>,
@@ -93,12 +141,12 @@ where
 {
     type Output = ();
 
-    fn apply_gradient(&mut self, grad: &ParamsBase<T, D>, lr: A) -> crate::Result<Self::Output> {
+    fn apply_gradient(&mut self, grad: &ParamsBase<T, D>, lr: A) -> Option<Self::Output> {
         // apply the bias gradient
         self.bias_mut().apply_gradient(grad.bias(), lr)?;
         // apply the weight gradient
         self.weights_mut().apply_gradient(grad.weights(), lr)?;
-        Ok(())
+        Some(())
     }
 
     fn apply_gradient_with_decay(
@@ -106,18 +154,18 @@ where
         grad: &ParamsBase<T, D>,
         lr: A,
         decay: A,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         // apply the bias gradient
         self.bias_mut()
             .apply_gradient_with_decay(grad.bias(), lr, decay)?;
         // apply the weight gradient
         self.weights_mut()
             .apply_gradient_with_decay(grad.weights(), lr, decay)?;
-        Ok(())
+        Some(())
     }
 }
 
-impl<A, S, T, D> ApplyGradientExt<ParamsBase<T, D>, A> for ParamsBase<S, D>
+impl<A, S, T, D> ApplyGradientExt<ParamsBase<T, D>, A> for ParamsBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: DataMut<Elem = A>,
@@ -132,7 +180,7 @@ where
         lr: A,
         momentum: A,
         velocity: &mut Self::Velocity,
-    ) -> crate::Result<()> {
+    ) -> Option<()> {
         // apply the bias gradient
         self.bias_mut().apply_gradient_with_momentum(
             grad.bias(),
@@ -147,7 +195,7 @@ where
             momentum,
             velocity.weights_mut(),
         )?;
-        Ok(())
+        Some(())
     }
 
     fn apply_gradient_with_decay_and_momentum(
@@ -157,7 +205,7 @@ where
         decay: A,
         momentum: A,
         velocity: &mut Self::Velocity,
-    ) -> crate::Result<()> {
+    ) -> Option<()> {
         // apply the bias gradient
         self.bias_mut().apply_gradient_with_decay_and_momentum(
             grad.bias(),
@@ -174,7 +222,7 @@ where
             momentum,
             velocity.weights_mut(),
         )?;
-        Ok(())
+        Some(())
     }
 }
 
@@ -192,7 +240,7 @@ where
         input: &ArrayBase<S, Ix2>,
         delta: &ArrayBase<T, Ix1>,
         gamma: Self::Elem,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         // compute the weight gradient
         let weight_delta = delta.t().dot(input);
         // update the weights and bias
@@ -200,11 +248,11 @@ where
         self.bias_mut()
             .apply_gradient(&delta.sum_axis(Axis(0)), gamma)?;
         // return the sum of the squared delta
-        Ok(delta.pow2().sum())
+        Some(delta.pow2().sum())
     }
 }
 
-impl<A, S, T> Backward<ArrayBase<S, Ix1>, ArrayBase<T, Ix0>> for Params<A, Ix1>
+impl<A, S, T> Backward<ArrayBase<S, Ix1, A>, ArrayBase<T, Ix0, A>> for Params<A, Ix1>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: Data<Elem = A>,
@@ -215,21 +263,21 @@ where
 
     fn backward(
         &mut self,
-        input: &ArrayBase<S, Ix1>,
-        delta: &ArrayBase<T, Ix0>,
+        input: &ArrayBase<S, Ix1, A>,
+        delta: &ArrayBase<T, Ix0, A>,
         gamma: Self::Elem,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         // compute the weight gradient
         let weight_delta = input * delta;
         // update the weights and bias
         self.weights_mut().apply_gradient(&weight_delta, gamma)?;
         self.bias_mut().apply_gradient(delta, gamma)?;
         // return the sum of the squared delta
-        Ok(delta.pow2().sum())
+        Some(delta.pow2().sum())
     }
 }
 
-impl<A, S, T> Backward<ArrayBase<S, Ix1>, ArrayBase<T, Ix1>> for Params<A, Ix2>
+impl<A, S, T> Backward<ArrayBase<S, Ix1, A>, ArrayBase<T, Ix1, A>> for Params<A, Ix2>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: Data<Elem = A>,
@@ -240,21 +288,21 @@ where
 
     fn backward(
         &mut self,
-        input: &ArrayBase<S, Ix1>,
-        delta: &ArrayBase<T, Ix1>,
+        input: &ArrayBase<S, Ix1, A>,
+        delta: &ArrayBase<T, Ix1, A>,
         gamma: Self::Elem,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         // compute the weight gradient
         let dw = &self.weights * delta.t().dot(input);
         // update the weights and bias
         self.weights_mut().apply_gradient(&dw, gamma)?;
         self.bias_mut().apply_gradient(delta, gamma)?;
         // return the sum of the squared delta
-        Ok(delta.pow2().sum())
+        Some(delta.pow2().sum())
     }
 }
 
-impl<A, S, T> Backward<ArrayBase<S, Ix2>, ArrayBase<T, Ix2>> for Params<A, Ix2>
+impl<A, S, T> Backward<ArrayBase<S, Ix2, A>, ArrayBase<T, Ix2, A>> for Params<A, Ix2>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: Data<Elem = A>,
@@ -265,10 +313,10 @@ where
 
     fn backward(
         &mut self,
-        input: &ArrayBase<S, Ix2>,
-        delta: &ArrayBase<T, Ix2>,
+        input: &ArrayBase<S, Ix2, A>,
+        delta: &ArrayBase<T, Ix2, A>,
         gamma: Self::Elem,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         // compute the weight gradient
         let weight_delta = input.dot(&delta.t());
         // compute the bias gradient
@@ -277,11 +325,13 @@ where
         self.weights_mut().apply_gradient(&weight_delta, gamma)?;
         self.bias_mut().apply_gradient(&bias_delta, gamma)?;
         // return the sum of the squared delta
-        Ok(delta.pow2().sum())
+        let y = input.dot(self.weights()) + self.bias();
+        let res = (&y - delta).pow2().sum();
+        Some(res)
     }
 }
 
-impl<A, X, Y, Z, S, D> Forward<X> for ParamsBase<S, D>
+impl<A, X, Y, Z, S, D> Forward<X> for ParamsBase<S, D, A>
 where
     A: Clone,
     D: Dimension,
@@ -291,8 +341,7 @@ where
 {
     type Output = Z;
 
-    fn forward(&self, input: &X) -> crate::Result<Self::Output> {
-        let output = input.dot(&self.weights) + &self.bias;
-        Ok(output)
+    fn forward(&self, input: &X) -> Option<Self::Output> {
+        Some(input.dot(self.weights()) + self.bias())
     }
 }
diff --git a/core/src/params/impls/impl_params_rand.rs b/params/src/impls/impl_params_rand.rs
similarity index 95%
rename from core/src/params/impls/impl_params_rand.rs
rename to params/src/impls/impl_params_rand.rs
index 9c81ec33..d61fd71f 100644
--- a/core/src/params/impls/impl_params_rand.rs
+++ b/params/src/impls/impl_params_rand.rs
@@ -8,7 +8,7 @@ use ndarray::{DataOwned, Dimension, RawData, RemoveAxis, ScalarOperand, ShapeBui
 use num_traits::{Float, FromPrimitive};
 use rand_distr::Distribution;
 
-impl<A, S, D> ParamsBase<S, D>
+impl<A, S, D> ParamsBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
diff --git a/core/src/params/impls/impl_params_serde.rs b/params/src/impls/impl_params_serde.rs
similarity index 93%
rename from core/src/params/impls/impl_params_serde.rs
rename to params/src/impls/impl_params_serde.rs
index 34421d75..07bce482 100644
--- a/core/src/params/impls/impl_params_serde.rs
+++ b/params/src/impls/impl_params_serde.rs
@@ -26,7 +26,7 @@ where
     A: Deserialize<'a>,
     <D as ndarray::Dimension>::Smaller: Deserialize<'a>,
 {
-    type Value = ParamsBase<S, D>;
+    type Value = ParamsBase<S, D, A>;
 
     fn expecting(&self, formatter: &mut std::fmt::Formatter) -> std::fmt::Result {
         formatter.write_str("a ParamsBase object")
@@ -47,7 +47,7 @@ where
     }
 }
 
-impl<'a, A, S, D> Deserialize<'a> for ParamsBase<S, D>
+impl<'a, A, S, D> Deserialize<'a> for ParamsBase<S, D, A>
 where
     D: Dimension + Deserialize<'a>,
     S: DataOwned<Elem = A>,
@@ -68,7 +68,7 @@ where
     }
 }
 
-impl<A, S, D> Serialize for ParamsBase<S, D>
+impl<A, S, D> Serialize for ParamsBase<S, D, A>
 where
     A: Serialize,
     D: Dimension + Serialize,
diff --git a/core/src/params/iter.rs b/params/src/iter.rs
similarity index 100%
rename from core/src/params/iter.rs
rename to params/src/iter.rs
diff --git a/core/src/params/mod.rs b/params/src/lib.rs
similarity index 56%
rename from core/src/params/mod.rs
rename to params/src/lib.rs
index 46ef101b..c1636594 100644
--- a/core/src/params/mod.rs
+++ b/params/src/lib.rs
@@ -10,12 +10,32 @@
 //!
 //! The associated types follow suite with the [`ndarray`] crate, each of which defines a
 //! different style of representation for the parameters.
+//!
+#![cfg_attr(not(feature = "std"), no_std)]
+#![allow(
+    clippy::missing_saftey_doc,
+    clippy::module_inception,
+    clippy::needless_doctest_main,
+    clippy::upper_case_acronyms
+)]
+
+#[cfg(feature = "alloc")]
+extern crate alloc;
+
+#[cfg(all(not(feature = "alloc"), not(feature = "std")))]
+compiler_error! {
+ "Either the \"alloc\" or \"std\" feature must be enabled for this crate."
+}
+
 #[doc(inline)]
-pub use self::{error::ParamsError, params::ParamsBase, types::*};
+pub use self::{error::*, params::ParamsBase, types::*};
+
+#[cfg(feature = "init")]
+extern crate concision_init as init;
 
-/// this module provides the [`ParamsError`] type for handling various errors within the module
+/// Error handling for parameters
 pub mod error;
-/// this module implements various iterators for the [`ParamsBase`]
+/// The [`iter`] module implements various iterators for parameters
 pub mod iter;
 
 mod params;
@@ -35,7 +55,7 @@ mod impls {
 }
 
 mod types {
-    //! this module defines various types and type aliases for the `params` module
+    //! Additional types supporting the params module
     #[doc(inline)]
     pub use self::prelude::*;
 
@@ -47,8 +67,9 @@ mod types {
     }
 }
 
-pub(crate) mod prelude {
-    pub use super::error::ParamsError;
-    pub use super::params::ParamsBase;
-    pub use super::types::*;
+#[doc(hidden)]
+pub mod prelude {
+    pub use crate::error::ParamsError;
+    pub use crate::params::*;
+    pub use crate::types::*;
 }
diff --git a/core/src/params/params.rs b/params/src/params.rs
similarity index 84%
rename from core/src/params/params.rs
rename to params/src/params.rs
index d3a3eff8..d62977f2 100644
--- a/core/src/params/params.rs
+++ b/params/src/params.rs
@@ -11,22 +11,22 @@ use ndarray::{
 /// model where the bias tensor is always `n-1` dimensions smaller than the `weights` tensor.
 /// Consequently, this constrains the [`ParamsBase`] implementation to only support dimensions
 /// that can be reduced by one axis (i.e. $`\mbox{rank}(D)>0`$), which is typically the "zero-th" axis.
-pub struct ParamsBase<S, D = ndarray::Ix2>
+pub struct ParamsBase<S, D = ndarray::Ix2, A = <S as RawData>::Elem>
 where
     D: Dimension,
-    S: RawData,
+    S: RawData<Elem = A>,
 {
-    pub(crate) bias: ArrayBase<S, D::Smaller>,
-    pub(crate) weights: ArrayBase<S, D>,
+    pub(crate) bias: ArrayBase<S, D::Smaller, A>,
+    pub(crate) weights: ArrayBase<S, D, A>,
 }
 
-impl<A, S, D> ParamsBase<S, D>
+impl<A, S, D> ParamsBase<S, D, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
 {
     /// create a new instance of the [`ParamsBase`] with the given bias and weights
-    pub const fn new(bias: ArrayBase<S, D::Smaller>, weights: ArrayBase<S, D>) -> Self {
+    pub const fn new(bias: ArrayBase<S, D::Smaller, A>, weights: ArrayBase<S, D, A>) -> Self {
         Self { bias, weights }
     }
     /// returns a new instance of the [`ParamsBase`] using the initialization routine
@@ -63,7 +63,7 @@ where
         Self::new(bias, weights)
     }
     /// create a new instance of the [`ParamsBase`] with the given bias used the default weights
-    pub fn from_bias<Sh>(shape: Sh, bias: ArrayBase<S, D::Smaller>) -> Self
+    pub fn from_bias<Sh>(shape: Sh, bias: ArrayBase<S, D::Smaller, A>) -> Self
     where
         A: Clone + Default,
         D: RemoveAxis,
@@ -75,7 +75,7 @@ where
     }
     /// create a new instance of the [`ParamsBase`] with the given weights used the default
     /// bias
-    pub fn from_weights<Sh>(shape: Sh, weights: ArrayBase<S, D>) -> Self
+    pub fn from_weights<Sh>(shape: Sh, weights: ArrayBase<S, D, A>) -> Self
     where
         A: Clone + Default,
         D: RemoveAxis,
@@ -132,23 +132,23 @@ where
         Self::from_elem(shape, A::zero())
     }
     /// returns an immutable reference to the bias
-    pub const fn bias(&self) -> &ArrayBase<S, D::Smaller> {
+    pub const fn bias(&self) -> &ArrayBase<S, D::Smaller, A> {
         &self.bias
     }
     /// returns a mutable reference to the bias
-    pub const fn bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller> {
+    pub const fn bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller, A> {
         &mut self.bias
     }
     /// returns an immutable reference to the weights
-    pub const fn weights(&self) -> &ArrayBase<S, D> {
+    pub const fn weights(&self) -> &ArrayBase<S, D, A> {
         &self.weights
     }
     /// returns a mutable reference to the weights
-    pub const fn weights_mut(&mut self) -> &mut ArrayBase<S, D> {
+    pub const fn weights_mut(&mut self) -> &mut ArrayBase<S, D, A> {
         &mut self.weights
     }
     /// assign the bias
-    pub fn assign_bias(&mut self, bias: &ArrayBase<S, D::Smaller>) -> &mut Self
+    pub fn assign_bias(&mut self, bias: &ArrayBase<S, D::Smaller, A>) -> &mut Self
     where
         A: Clone,
         S: DataMut,
@@ -157,7 +157,7 @@ where
         self
     }
     /// assign the weights
-    pub fn assign_weights(&mut self, weights: &ArrayBase<S, D>) -> &mut Self
+    pub fn assign_weights(&mut self, weights: &ArrayBase<S, D, A>) -> &mut Self
     where
         A: Clone,
         S: DataMut,
@@ -166,41 +166,26 @@ where
         self
     }
     /// replace the bias and return the previous state; uses [replace](core::mem::replace)
-    pub fn replace_bias(&mut self, bias: ArrayBase<S, D::Smaller>) -> ArrayBase<S, D::Smaller> {
+    pub fn replace_bias(
+        &mut self,
+        bias: ArrayBase<S, D::Smaller, A>,
+    ) -> ArrayBase<S, D::Smaller, A> {
         core::mem::replace(&mut self.bias, bias)
     }
     /// replace the weights and return the previous state; uses [replace](core::mem::replace)
-    pub fn replace_weights(&mut self, weights: ArrayBase<S, D>) -> ArrayBase<S, D> {
+    pub fn replace_weights(&mut self, weights: ArrayBase<S, D, A>) -> ArrayBase<S, D, A> {
         core::mem::replace(&mut self.weights, weights)
     }
     /// set the bias
-    pub fn set_bias(&mut self, bias: ArrayBase<S, D::Smaller>) -> &mut Self {
+    pub fn set_bias(&mut self, bias: ArrayBase<S, D::Smaller, A>) -> &mut Self {
         *self.bias_mut() = bias;
         self
     }
     /// set the weights
-    pub fn set_weights(&mut self, weights: ArrayBase<S, D>) -> &mut Self {
+    pub fn set_weights(&mut self, weights: ArrayBase<S, D, A>) -> &mut Self {
         *self.weights_mut() = weights;
         self
     }
-    /// perform a single backpropagation step
-    pub fn backward<X, Y, Z>(&mut self, input: &X, grad: &Y, lr: A) -> crate::Result<Z>
-    where
-        A: Clone,
-        S: Data,
-        Self: crate::Backward<X, Y, Elem = A, Output = Z>,
-    {
-        <Self as crate::Backward<X, Y>>::backward(self, input, grad, lr)
-    }
-    /// forward propagation
-    pub fn forward<X, Y>(&self, input: &X) -> crate::Result<Y>
-    where
-        A: Clone,
-        S: Data,
-        Self: crate::Forward<X, Output = Y>,
-    {
-        <Self as crate::Forward<X>>::forward(self, input)
-    }
     /// returns the dimensions of the weights
     pub fn dim(&self) -> D::Pattern {
         self.weights().dim()
@@ -230,13 +215,19 @@ where
         self.weights().raw_dim()
     }
     /// returns the shape of the parameters; uses the shape of the weight tensor
-    pub fn shape(&self) -> &[usize] {
-        self.weights().shape()
+    pub fn shape<'a>(&'a self) -> &'a [usize]
+    where
+        A: 'a,
+    {
+        self.weights.shape()
     }
     /// returns the shape of the bias tensor; the shape should be equivalent to that of the
     /// weight tensor minus the "zero-th" axis
-    pub fn shape_bias(&self) -> &[usize] {
-        self.bias().shape()
+    pub fn shape_bias(&self) -> &[usize]
+    where
+        A: 'static,
+    {
+        self.bias.shape()
     }
     /// returns the total number of parameters within the layer
     pub fn size(&self) -> usize {
diff --git a/core/src/params/types/aliases.rs b/params/src/types/aliases.rs
similarity index 84%
rename from core/src/params/types/aliases.rs
rename to params/src/types/aliases.rs
index e8b33189..fed92869 100644
--- a/core/src/params/types/aliases.rs
+++ b/params/src/types/aliases.rs
@@ -7,18 +7,18 @@ use crate::params::ParamsBase;
 use ndarray::{CowRepr, Ix2, OwnedArcRepr, OwnedRepr, RawViewRepr, ViewRepr};
 
 /// A type alias for a [`ParamsBase`] with an owned internal layout
-pub type Params<A, D = Ix2> = ParamsBase<OwnedRepr<A>, D>;
+pub type Params<A, D = Ix2> = ParamsBase<OwnedRepr<A>, D, A>;
 /// A type alias for shared parameters
-pub type ArcParams<A, D = Ix2> = ParamsBase<OwnedArcRepr<A>, D>;
+pub type ArcParams<A, D = Ix2> = ParamsBase<OwnedArcRepr<A>, D, A>;
 /// A type alias for an immutable view of the parameters
-pub type ParamsView<'a, A, D = Ix2> = ParamsBase<ViewRepr<&'a A>, D>;
+pub type ParamsView<'a, A, D = Ix2> = ParamsBase<ViewRepr<&'a A>, D, A>;
 /// A type alias for a mutable view of the parameters
-pub type ParamsViewMut<'a, A, D = Ix2> = ParamsBase<ViewRepr<&'a mut A>, D>;
+pub type ParamsViewMut<'a, A, D = Ix2> = ParamsBase<ViewRepr<&'a mut A>, D, A>;
 /// A type alias for a [`ParamsBase`] with a _borrowed_ internal layout
-pub type CowParams<'a, A, D = Ix2> = ParamsBase<CowRepr<'a, A>, D>;
+pub type CowParams<'a, A, D = Ix2> = ParamsBase<CowRepr<'a, A>, D, A>;
 /// A type alias for the [`ParamsBase`] whose elements are of type `*const A` using a
 /// [`RawViewRepr`] layout
-pub type RawViewParams<A, D = Ix2> = ParamsBase<RawViewRepr<*const A>, D>;
+pub type RawViewParams<A, D = Ix2> = ParamsBase<RawViewRepr<*const A>, D, A>;
 /// A type alias for the [`ParamsBase`] whose elements are of type `*mut A` using a
 /// [`RawViewRepr`] layout
-pub type RawMutParams<A, D = Ix2> = ParamsBase<RawViewRepr<*mut A>, D>;
+pub type RawMutParams<A, D = Ix2> = ParamsBase<RawViewRepr<*mut A>, D, A>;
diff --git a/params/tests/default.rs b/params/tests/default.rs
new file mode 100644
index 00000000..233a07af
--- /dev/null
+++ b/params/tests/default.rs
@@ -0,0 +1,17 @@
+/*
+    Appellation: default <test>
+    Contrib: FL03 <jo3mccain@icloud.com>
+*/
+
+fn add<A, B, C>(a: A, b: B) -> C
+where
+    A: core::ops::Add<B, Output = C>,
+{
+    a + b
+}
+
+#[test]
+fn compiles() {
+    assert_eq!(add(10, 10), 20);
+    assert_ne!(add(1, 1), 3);
+}
diff --git a/params/tests/params.rs b/params/tests/params.rs
new file mode 100644
index 00000000..5dba0707
--- /dev/null
+++ b/params/tests/params.rs
@@ -0,0 +1,52 @@
+/*
+    Appellation: params <test>
+    Contrib: @FL03
+*/
+extern crate concision_params as cnc;
+use concision_params::Params;
+
+#[test]
+fn test_params_ones() {
+    // weights retain the given shape (d_in, d_out)
+    // bias retains the shape (d_out,)
+    let ones = Params::<f64>::ones((3, 4));
+    assert_eq!(ones.dim(), (3, 4));
+    assert_eq!(ones.bias().dim(), 4);
+    assert!(
+        ones.iter()
+            .all(|(w, b)| w.iter().all(|&wi| wi == 1.0) && b == &1.0)
+    );
+}
+
+#[test]
+fn test_params_zeros() {
+    // weights retain the given shape (d_in, d_out)
+    // bias retains the shape (d_out,)
+    let zeros = Params::<f64>::zeros((3, 4));
+    assert_eq!(zeros.dim(), (3, 4));
+    assert_eq!(zeros.bias().dim(), 4);
+    assert!(
+        zeros
+            .iter()
+            .all(|(w, b)| w.iter().all(|&wi| wi == 0.0) && b == &0.0)
+    );
+}
+
+#[test]
+#[cfg(feature = "init")]
+fn test_params_init() {
+    use concision_init::Initialize;
+
+    let lecun = Params::<f64>::lecun_normal((3, 4));
+    assert_eq!(lecun.dim(), (3, 4));
+
+    let glorot_norm = Params::<f64>::glorot_normal((3, 4));
+    assert_eq!(glorot_norm.dim(), (3, 4));
+    assert_ne!(lecun, glorot_norm);
+    let glorot_uniform = Params::<f64>::glorot_uniform((3, 4)).expect("glorot_uniform failed");
+    assert_eq!(glorot_uniform.dim(), (3, 4));
+    assert_ne!(lecun, glorot_uniform);
+    assert_ne!(glorot_norm, glorot_uniform);
+    let truncnorm = Params::<f64>::truncnorm((3, 4), 0.0, 1.0).expect("truncnorm failed");
+    assert_eq!(truncnorm.dim(), (3, 4));
+}
diff --git a/traits/Cargo.toml b/traits/Cargo.toml
new file mode 100644
index 00000000..9a1687a7
--- /dev/null
+++ b/traits/Cargo.toml
@@ -0,0 +1,91 @@
+[package]
+build = "build.rs"
+description = "this crate implements the core modules for the concision framework"
+name = "concision-traits"
+
+authors.workspace = true
+categories.workspace = true
+edition.workspace = true
+homepage.workspace = true
+keywords.workspace = true
+license.workspace = true
+readme.workspace = true
+repository.workspace = true
+rust-version.workspace = true
+version.workspace = true
+
+[package.metadata.docs.rs]
+all-features = false
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
+
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
+
+[lib]
+bench = false
+crate-type = ["cdylib", "rlib"]
+doc = true
+doctest = true
+test = true
+
+[dependencies]
+# custom
+variants = { workspace = true }
+# error-handling
+thiserror = { workspace = true }
+# macros & utilities
+paste = { workspace = true }
+# mathematics
+approx = { optional = true, workspace = true }
+ndarray = { workspace = true }
+num-complex = { optional = true, workspace = true }
+num-traits = { workspace = true }
+# random
+getrandom = { default-features = false, optional = true, workspace = true }
+rand = { optional = true, workspace = true }
+rand_distr = { optional = true, workspace = true }
+
+[dev-dependencies]
+lazy_static = { workspace = true }
+
+[features]
+default = ["std"]
+
+full = [
+  "default",
+  "approx", 
+  "complex",
+  "rand",
+]
+
+nightly = []
+
+
+# ************* [FF:Dependencies] *************
+std = [
+  "alloc", "ndarray/std", 
+  "num-complex?/std", 
+  "num-traits/std", 
+  "rand?/std", 
+  "rand?/std_rng",
+  "thiserror/std"
+]
+
+wasi = []
+
+wasm = ["getrandom?/wasm_js"]
+# ************* [FF:Dependencies] *************
+alloc = []
+
+approx = ["dep:approx", "ndarray/approx"]
+
+blas = ["ndarray/blas"]
+
+complex = ["dep:num-complex"]
+
+rand = ["dep:rand", "dep:rand_distr", "num-complex?/rand", "rng"]
+
+rng = ["dep:getrandom", "rand?/small_rng", "rand?/thread_rng"]
diff --git a/traits/build.rs b/traits/build.rs
new file mode 100644
index 00000000..940a4ce4
--- /dev/null
+++ b/traits/build.rs
@@ -0,0 +1,8 @@
+/*
+    Appellation: build <build>
+    Contrib: FL03 <jo3mccain@icloud.com>
+*/
+
+fn main() {
+    println!("cargo::rustc-check-cfg=cfg(no_std)");
+}
diff --git a/core/src/traits/apply.rs b/traits/src/apply.rs
similarity index 88%
rename from core/src/traits/apply.rs
rename to traits/src/apply.rs
index 3bd6cafc..75da1b81 100644
--- a/core/src/traits/apply.rs
+++ b/traits/src/apply.rs
@@ -61,7 +61,6 @@ pub trait ApplyMut<T> {
  ************* Implementations *************
 */
 use ndarray::{Array, ArrayBase, Data, DataMut, Dimension, ScalarOperand};
-use ndtensor::{Tensor, TensorBase};
 
 impl<T> CallInto<T> for T {
     type Output = T;
@@ -98,7 +97,7 @@ where
     }
 }
 
-impl<A, S, D> Apply<A> for ArrayBase<S, D>
+impl<A, S, D> Apply<A> for ArrayBase<S, D, A>
 where
     A: ScalarOperand,
     D: Dimension,
@@ -114,23 +113,23 @@ where
     }
 }
 
-impl<A, S, D> Apply<A> for TensorBase<S, D>
-where
-    A: ScalarOperand,
-    D: Dimension,
-    S: Data<Elem = A>,
-{
-    type Cont<V> = Tensor<V, D>;
-
-    fn apply<V, F>(&self, f: F) -> Self::Cont<V>
-    where
-        F: Fn(A) -> V,
-    {
-        self.map(f)
-    }
-}
-
-impl<A, S, D> Apply<A> for &ArrayBase<S, D>
+// impl<A, S, D> Apply<A> for TensorBase<S, D>
+// where
+//     A: ScalarOperand,
+//     D: Dimension,
+//     S: Data<Elem = A>,
+// {
+//     type Cont<V> = Tensor<V, D>;
+
+//     fn apply<V, F>(&self, f: F) -> Self::Cont<V>
+//     where
+//         F: Fn(A) -> V,
+//     {
+//         self.map(f)
+//     }
+// }
+
+impl<A, S, D> Apply<A> for &ArrayBase<S, D, A>
 where
     A: ScalarOperand,
     D: Dimension,
@@ -146,7 +145,7 @@ where
     }
 }
 
-impl<A, S, D> Apply<A> for &mut ArrayBase<S, D>
+impl<A, S, D> Apply<A> for &mut ArrayBase<S, D, A>
 where
     A: ScalarOperand,
     D: Dimension,
@@ -162,7 +161,7 @@ where
     }
 }
 
-impl<A, S, D> ApplyMut<A> for ArrayBase<S, D>
+impl<A, S, D> ApplyMut<A> for ArrayBase<S, D, A>
 where
     A: ScalarOperand,
     D: Dimension,
@@ -179,7 +178,7 @@ where
     }
 }
 
-impl<A, S, D> ApplyMut<A> for &mut ArrayBase<S, D>
+impl<A, S, D> ApplyMut<A> for &mut ArrayBase<S, D, A>
 where
     A: ScalarOperand,
     D: Dimension,
diff --git a/core/src/traits/clip.rs b/traits/src/clip.rs
similarity index 96%
rename from core/src/traits/clip.rs
rename to traits/src/clip.rs
index c237833d..8a17a55f 100644
--- a/core/src/traits/clip.rs
+++ b/traits/src/clip.rs
@@ -38,11 +38,11 @@ pub trait ClipMut<T = f32> {
 /*
  ************* Implementations *************
 */
-use crate::ops::{L1Norm, L2Norm};
+use crate::norm::{L1Norm, L2Norm};
 use ndarray::{ArrayBase, Dimension, ScalarOperand};
 use num_traits::Float;
 
-impl<A, S, D> Clip<A> for ArrayBase<S, D>
+impl<A, S, D> Clip<A> for ArrayBase<S, D, A>
 where
     A: 'static + Clone + PartialOrd,
     S: ndarray::Data<Elem = A>,
@@ -55,7 +55,7 @@ where
     }
 }
 
-impl<A, S, D> ClipMut<A> for ArrayBase<S, D>
+impl<A, S, D> ClipMut<A> for ArrayBase<S, D, A>
 where
     A: Float + ScalarOperand,
     S: ndarray::DataMut<Elem = A>,
diff --git a/core/src/traits/codex.rs b/traits/src/codex.rs
similarity index 100%
rename from core/src/traits/codex.rs
rename to traits/src/codex.rs
diff --git a/core/src/traits/convert.rs b/traits/src/convert.rs
similarity index 100%
rename from core/src/traits/convert.rs
rename to traits/src/convert.rs
diff --git a/core/src/traits/entropy.rs b/traits/src/entropy.rs
similarity index 89%
rename from core/src/traits/entropy.rs
rename to traits/src/entropy.rs
index e59aec4c..3562375c 100644
--- a/core/src/traits/entropy.rs
+++ b/traits/src/entropy.rs
@@ -29,7 +29,7 @@ pub trait MeanSquaredError {
 use ndarray::{ArrayBase, Data, Dimension, ScalarOperand};
 use num_traits::{Float, FromPrimitive};
 
-impl<A, S, D> CrossEntropy for ArrayBase<S, D>
+impl<A, S, D> CrossEntropy for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
@@ -42,7 +42,7 @@ where
     }
 }
 
-impl<A, S, D> MeanAbsoluteError for ArrayBase<S, D>
+impl<A, S, D> MeanAbsoluteError for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
@@ -55,7 +55,7 @@ where
     }
 }
 
-impl<A, S, D> MeanSquaredError for ArrayBase<S, D>
+impl<A, S, D> MeanSquaredError for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     D: Dimension,
diff --git a/traits/src/error.rs b/traits/src/error.rs
new file mode 100644
index 00000000..568cc1a7
--- /dev/null
+++ b/traits/src/error.rs
@@ -0,0 +1,49 @@
+/*
+    Appellation: error <module>
+    Contrib: @FL03
+*/
+//! This module implements the core [`Error`] type for the framework and provides a [`Result`]
+//! type alias for convenience.
+#[cfg(feature = "alloc")]
+use alloc::{boxed::Box, string::String};
+
+#[allow(dead_code)]
+/// a type alias for a [Result](core::result::Result) configured with an [`Error`] as its error
+/// type.
+pub type Result<T> = core::result::Result<T, Error>;
+
+/// The [`Error`] type enumerates various errors that can occur within the framework.
+#[derive(Debug, thiserror::Error)]
+#[non_exhaustive]
+pub enum Error {
+    #[error(transparent)]
+    FmtError(#[from] core::fmt::Error),
+    #[cfg(feature = "std")]
+    #[error(transparent)]
+    IoError(#[from] std::io::Error),
+    #[error(transparent)]
+    ShapeError(#[from] ndarray::ShapeError),
+    #[error(transparent)]
+    #[cfg(feature = "rand")]
+    UniformError(#[from] rand_distr::uniform::Error),
+    #[cfg(feature = "alloc")]
+    #[error(transparent)]
+    BoxError(#[from] Box<dyn core::error::Error + Send + Sync>),
+    #[cfg(feature = "alloc")]
+    #[error("Unknown Error: {0}")]
+    Unknown(String),
+}
+
+#[cfg(feature = "alloc")]
+impl From<String> for Error {
+    fn from(value: String) -> Self {
+        Self::Unknown(value)
+    }
+}
+
+#[cfg(feature = "alloc")]
+impl From<&str> for Error {
+    fn from(value: &str) -> Self {
+        String::from(value).into()
+    }
+}
diff --git a/core/src/ops/fill.rs b/traits/src/fill.rs
similarity index 87%
rename from core/src/ops/fill.rs
rename to traits/src/fill.rs
index d50d95a5..0c765ef9 100644
--- a/core/src/ops/fill.rs
+++ b/traits/src/fill.rs
@@ -26,14 +26,14 @@ pub trait IsSquare {
  ******** implementations ********
 */
 
-impl<A, S, D> MaskFill<A, D> for ArrayBase<S, D>
+impl<A, S, D> MaskFill<A, D> for ArrayBase<S, D, A>
 where
     A: Clone,
     D: Dimension,
     S: DataMut<Elem = A>,
     Self: Clone,
 {
-    type Output = ArrayBase<S, D>;
+    type Output = ArrayBase<S, D, A>;
 
     fn masked_fill(&self, mask: &Array<bool, D>, value: A) -> Self::Output {
         let mut arr = self.clone();
@@ -46,10 +46,10 @@ where
     }
 }
 
-impl<S, D> IsSquare for ArrayBase<S, D>
+impl<A, S, D> IsSquare for ArrayBase<S, D, A>
 where
     D: Dimension,
-    S: RawData,
+    S: RawData<Elem = A>,
 {
     fn is_square(&self) -> bool {
         let first = self.shape().first().unwrap();
diff --git a/core/src/traits/gradient.rs b/traits/src/gradient.rs
similarity index 76%
rename from core/src/traits/gradient.rs
rename to traits/src/gradient.rs
index 22360389..1e3d957a 100644
--- a/core/src/traits/gradient.rs
+++ b/traits/src/gradient.rs
@@ -17,14 +17,9 @@ pub trait Gradient<T, D> {
 pub trait ApplyGradient<Delta, T> {
     type Output;
 
-    fn apply_gradient(&mut self, grad: &Delta, lr: T) -> crate::Result<Self::Output>;
+    fn apply_gradient(&mut self, grad: &Delta, lr: T) -> Option<Self::Output>;
 
-    fn apply_gradient_with_decay(
-        &mut self,
-        grad: &Delta,
-        lr: T,
-        decay: T,
-    ) -> crate::Result<Self::Output>;
+    fn apply_gradient_with_decay(&mut self, grad: &Delta, lr: T, decay: T) -> Option<Self::Output>;
 }
 
 /// This trait extends the [ApplyGradient] trait by allowing for momentum-based optimization
@@ -37,7 +32,7 @@ pub trait ApplyGradientExt<Delta, T>: ApplyGradient<Delta, T> {
         lr: T,
         momentum: T,
         velocity: &mut Self::Velocity,
-    ) -> crate::Result<Self::Output>;
+    ) -> Option<Self::Output>;
 
     fn apply_gradient_with_decay_and_momentum(
         &mut self,
@@ -46,17 +41,17 @@ pub trait ApplyGradientExt<Delta, T>: ApplyGradient<Delta, T> {
         decay: T,
         momentum: T,
         velocity: &mut Self::Velocity,
-    ) -> crate::Result<Self::Output>;
+    ) -> Option<Self::Output>;
 }
 
 /*
  ************* Implementations *************
 */
 
-use ndarray::{Array, ArrayBase, Data, DataMut, Dimension, ScalarOperand, ShapeError};
+use ndarray::{Array, ArrayBase, Data, DataMut, Dimension, ScalarOperand};
 use num_traits::{Float, FromPrimitive};
 
-impl<A, S, T, D> ApplyGradient<ArrayBase<T, D>, A> for ArrayBase<S, D>
+impl<A, S, T, D> ApplyGradient<ArrayBase<T, D>, A> for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: DataMut<Elem = A>,
@@ -65,9 +60,10 @@ where
 {
     type Output = ();
 
-    fn apply_gradient(&mut self, grad: &ArrayBase<T, D>, lr: A) -> crate::Result<Self::Output> {
+    fn apply_gradient(&mut self, grad: &ArrayBase<T, D>, lr: A) -> Option<Self::Output> {
         if self.shape() != grad.shape() {
-            return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            // return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            return None;
         }
         let batch_size = if !grad.shape().is_empty() {
             A::from_usize(self.shape()[0]).unwrap()
@@ -75,7 +71,7 @@ where
             A::one()
         };
         self.scaled_add(lr / batch_size, grad);
-        Ok(())
+        Some(())
     }
 
     fn apply_gradient_with_decay(
@@ -83,21 +79,23 @@ where
         grad: &ArrayBase<T, D>,
         lr: A,
         decay: A,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         if self.shape() != grad.shape() {
-            return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            // return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            return None;
         }
         let batch_size = if !grad.shape().is_empty() {
             A::from_usize(self.shape()[0]).unwrap()
         } else {
             A::one()
         };
-        self.scaled_add(lr / batch_size, &(grad + &*self * decay));
-        Ok(())
+        let rhs = grad + &*self * decay;
+        self.scaled_add(lr / batch_size, &rhs);
+        Some(())
     }
 }
 
-impl<A, S, T, D> ApplyGradientExt<ArrayBase<T, D>, A> for ArrayBase<S, D>
+impl<A, S, T, D> ApplyGradientExt<ArrayBase<T, D>, A> for ArrayBase<S, D, A>
 where
     A: Float + FromPrimitive + ScalarOperand,
     S: DataMut<Elem = A>,
@@ -112,9 +110,10 @@ where
         lr: A,
         momentum: A,
         velocity: &mut Self::Velocity,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         if self.shape() != grad.shape() {
-            return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            // return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            return None;
         }
         let batch_size = if !grad.shape().is_empty() {
             A::from_usize(self.shape()[0]).unwrap()
@@ -123,7 +122,7 @@ where
         };
         *velocity = &*velocity * momentum + grad * (A::one() - momentum);
         self.scaled_add(lr / batch_size, velocity);
-        Ok(())
+        Some(())
     }
 
     fn apply_gradient_with_decay_and_momentum(
@@ -133,11 +132,10 @@ where
         decay: A,
         momentum: A,
         velocity: &mut Self::Velocity,
-    ) -> crate::Result<Self::Output> {
+    ) -> Option<Self::Output> {
         if self.shape() != grad.shape() {
-            return Err(
-                ndarray::ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into(),
-            );
+            // return Err(ShapeError::from_kind(ndarray::ErrorKind::IncompatibleShape).into());
+            return None;
         }
         let batch_size = if !grad.shape().is_empty() {
             A::from_usize(self.shape()[0]).unwrap()
@@ -148,6 +146,6 @@ where
         let adjusted_grad = grad + &*self * decay;
         *velocity = &*velocity * momentum + adjusted_grad * (A::one() - momentum);
         self.scaled_add(lr / batch_size, velocity);
-        Ok(())
+        Some(())
     }
 }
diff --git a/traits/src/lib.rs b/traits/src/lib.rs
new file mode 100644
index 00000000..e69b0d1f
--- /dev/null
+++ b/traits/src/lib.rs
@@ -0,0 +1,69 @@
+/*
+    Appellation: concision-traits <library>
+    Contrib: @FL03
+*/
+//! Traits for the concicion machine learning framework
+#![allow(
+    clippy::missing_safety_doc,
+    clippy::module_inception,
+    clippy::needless_doctest_main,
+    clippy::upper_case_acronyms
+)]
+#![cfg_attr(not(feature = "std"), no_std)]
+#![cfg_attr(feature = "nightly", feature(allocator_api))]
+#![crate_type = "lib"]
+
+#[cfg(not(all(feature = "std", feature = "alloc")))]
+compiler_error! {
+    "At least one of the 'std' or 'alloc' features must be enabled."
+}
+
+#[cfg(feature = "alloc")]
+extern crate alloc;
+
+#[macro_use]
+pub(crate) mod macros {
+    #[macro_use]
+    pub mod seal;
+}
+
+pub mod error;
+
+mod apply;
+mod clip;
+mod codex;
+mod convert;
+mod fill;
+mod gradient;
+mod like;
+mod norm;
+mod propagation;
+mod reshape;
+mod shape;
+mod store;
+mod tensor_ops;
+mod wnb;
+
+// re-exports
+#[doc(inline)]
+pub use self::error::*;
+#[doc(inline)]
+pub use self::prelude::*;
+
+#[doc(hidden)]
+pub mod prelude {
+    pub use crate::apply::*;
+    pub use crate::clip::*;
+    pub use crate::codex::*;
+    pub use crate::convert::*;
+    pub use crate::fill::*;
+    pub use crate::gradient::*;
+    pub use crate::like::*;
+    pub use crate::norm::*;
+    pub use crate::propagation::*;
+    pub use crate::reshape::*;
+    pub use crate::shape::*;
+    pub use crate::store::*;
+    pub use crate::tensor_ops::*;
+    pub use crate::wnb::*;
+}
diff --git a/core/src/traits/like.rs b/traits/src/like.rs
similarity index 87%
rename from core/src/traits/like.rs
rename to traits/src/like.rs
index 2d168d7e..5baddb54 100644
--- a/core/src/traits/like.rs
+++ b/traits/src/like.rs
@@ -3,7 +3,7 @@
    Contrib: FL03 <jo3mccain@icloud.com>
 */
 use ndarray::{ArrayBase, DataOwned, Dimension, Ix2, ShapeBuilder};
-use num::traits::{Num, One, Zero};
+use num_traits::{Num, One, Zero};
 
 pub trait NdLike<A = f64, D = Ix2>
 where
@@ -60,13 +60,13 @@ ndlike! {
 /*
  ************* Implementations *************
 */
-impl<A, S, D> NdLike<A, D> for ArrayBase<S, D>
+impl<A, S, D> NdLike<A, D> for ArrayBase<S, D, A>
 where
     A: Clone + Num,
     D: Dimension,
     S: DataOwned<Elem = A>,
 {
-    type Output = ArrayBase<S, D>;
+    type Output = ArrayBase<S, D, A>;
 
     fn default_like(&self) -> Self::Output
     where
@@ -90,13 +90,13 @@ where
     }
 }
 
-impl<A, S, D> ArrayLike<A, D> for ArrayBase<S, D>
+impl<A, S, D> ArrayLike<A, D> for ArrayBase<S, D, A>
 where
     A: Clone,
     D: Dimension,
     S: ndarray::DataOwned<Elem = A>,
 {
-    type Output = ArrayBase<S, D>;
+    type Output = ArrayBase<S, D, A>;
 
     fn array_like<Sh>(&self, shape: Sh, elem: A) -> Self::Output
     where
@@ -110,13 +110,13 @@ where
     }
 }
 
-impl<A, S, D> FillLike<A> for ArrayBase<S, D>
+impl<A, S, D> FillLike<A> for ArrayBase<S, D, A>
 where
     A: Clone,
     D: Dimension,
     S: DataOwned<Elem = A>,
 {
-    type Output = ArrayBase<S, D>;
+    type Output = ArrayBase<S, D, A>;
 
     fn fill_like(&self, elem: A) -> Self::Output {
         ArrayBase::from_elem(self.dim(), elem)
@@ -126,13 +126,13 @@ where
 macro_rules! impl_ndlike {
 
     ($name:ident::$method:ident.$call:ident: $($p:tt)*) => {
-        impl<A, S, D> $name for ArrayBase<S, D>
+        impl<A, S, D> $name for ArrayBase<S, D, A>
         where
             A: $($p)*,
             D: Dimension,
             S: DataOwned<Elem = A>,
         {
-            type Output = ArrayBase<S, D>;
+            type Output = ArrayBase<S, D, A>;
 
             fn $method(&self) -> Self::Output {
                 ArrayBase::$call(self.dim())
diff --git a/traits/src/macros/seal.rs b/traits/src/macros/seal.rs
new file mode 100644
index 00000000..05f2bbf6
--- /dev/null
+++ b/traits/src/macros/seal.rs
@@ -0,0 +1,50 @@
+/*
+    Appellation: seal <module>
+    Contrib: FL03 <jo3mccain@icloud.com>
+*/
+//! The public parts of this private module are used to create traits
+//! that cannot be implemented outside of our own crate.  This way we
+//! can feel free to extend those traits without worrying about it
+//! being a breaking change for other implementations.
+//!
+//! ## Usage
+//!
+//! To define a private trait, you can use the [`private!`] macro, which will define a hidden
+//! method `__private__` that can only be implemented within the crate.
+
+/// If this type is pub but not publicly reachable, third parties
+/// can't name it and can't implement traits using it.
+#[allow(dead_code)]
+pub struct Seal;
+/// the [`private!`] macro is used to seal a particular trait, defining a hidden method that
+/// may only be implemented within the bounds of the crate.
+#[allow(unused_macros)]
+macro_rules! private {
+    () => {
+        /// This trait is private to implement; this method exists to make it
+        /// impossible to implement outside the crate.
+        #[doc(hidden)]
+        fn __private__(&self) -> $crate::macros::seal::Seal;
+    };
+}
+/// the [`seal!`] macro is used to implement a private method on a type, which is used to seal
+/// the type so that it cannot be implemented outside of the crate.
+#[allow(unused_macros)]
+macro_rules! seal {
+    () => {
+        fn __private__(&self) -> $crate::macros::seal::Seal {
+            $crate::macros::seal::Seal
+        }
+    };
+}
+/// this macros is used to implement a trait for a type, sealing it so that
+/// it cannot be implemented outside of the crate. This is most usefuly for creating other
+/// macros that can be used to implement some raw, sealed trait on the given _types_.
+#[allow(unused_macros)]
+macro_rules! sealed {
+    (impl$(<$($T:ident),*>)? $trait:ident for $name:ident$(<$($V:ident),*>)? $(where $($rest:tt)*)?) => {
+        impl$(<$($T),*>)? $trait for $name$(<$($V),*>)? $(where $($rest)*)? {
+            seal!();
+        }
+    };
+}
diff --git a/core/src/ops/norm/l_norm.rs b/traits/src/norm.rs
similarity index 92%
rename from core/src/ops/norm/l_norm.rs
rename to traits/src/norm.rs
index 93494f31..e4d9da00 100644
--- a/core/src/ops/norm/l_norm.rs
+++ b/traits/src/norm.rs
@@ -48,7 +48,7 @@ where
 
 macro_rules! impl_norm {
     ($trait:ident::$method:ident($($param:ident: $type:ty),*) => $self:ident$(.$call:ident())*) => {
-        impl<A, S, D> $trait for ArrayBase<S, D>
+        impl<A, S, D> $trait for ArrayBase<S, D, A>
         where
             A: Float + ScalarOperand,
             D: Dimension,
@@ -61,7 +61,7 @@ macro_rules! impl_norm {
             }
         }
 
-        impl<'a, A, S, D> $trait for &'a ArrayBase<S, D>
+        impl<'a, A, S, D> $trait for &'a ArrayBase<S, D, A>
         where
             A: Float + ScalarOperand,
             D: Dimension,
@@ -74,7 +74,7 @@ macro_rules! impl_norm {
             }
         }
 
-        impl<'a, A, S, D> $trait for &'a mut ArrayBase<S, D>
+        impl<'a, A, S, D> $trait for &'a mut ArrayBase<S, D, A>
         where
             A: Float + ScalarOperand,
             D: Dimension,
diff --git a/core/src/traits/propagation.rs b/traits/src/propagation.rs
similarity index 70%
rename from core/src/traits/propagation.rs
rename to traits/src/propagation.rs
index d36a6b7f..38a6bbc1 100644
--- a/core/src/traits/propagation.rs
+++ b/traits/src/propagation.rs
@@ -8,23 +8,18 @@ pub trait Backward<X, Delta = X> {
     type Elem;
     type Output;
 
-    fn backward(
-        &mut self,
-        input: &X,
-        delta: &Delta,
-        gamma: Self::Elem,
-    ) -> crate::Result<Self::Output>;
+    fn backward(&mut self, input: &X, delta: &Delta, gamma: Self::Elem) -> Option<Self::Output>;
 }
 
 /// This trait denotes entities capable of performing a single forward step
 pub trait Forward<Rhs> {
     type Output;
     /// a single forward step
-    fn forward(&self, input: &Rhs) -> crate::Result<Self::Output>;
+    fn forward(&self, input: &Rhs) -> Option<Self::Output>;
     /// this method enables the forward pass to be generically _activated_ using some closure.
     /// This is useful for isolating the logic of the forward pass from that of the activation
     /// function and is often used by layers and models.
-    fn forward_then<F>(&self, input: &Rhs, then: F) -> crate::Result<Self::Output>
+    fn forward_then<F>(&self, input: &Rhs, then: F) -> Option<Self::Output>
     where
         F: FnOnce(Self::Output) -> Self::Output,
     {
@@ -38,7 +33,7 @@ pub trait Forward<Rhs> {
 
 use ndarray::linalg::Dot;
 use ndarray::{ArrayBase, Data, Dimension};
-// impl<X, Y, Dx, A, S, D> Backward<X, Y> for ArrayBase<S, D>
+// impl<X, Y, Dx, A, S, D> Backward<X, Y> for ArrayBase<S, D, A>
 // where
 //     A: LinalgScalar + FromPrimitive,
 //     D: Dimension,
@@ -56,7 +51,7 @@ use ndarray::{ArrayBase, Data, Dimension};
 //         input: &X,
 //         delta: &Y,
 //         gamma: Self::Elem,
-//     ) -> crate::Result<Self::Output> {
+//     ) -> Option<Self::Output> {
 //         let grad = input.dot(delta);
 //         let next = &self + grad * gamma;
 //         self.assign(&next)?;
@@ -65,17 +60,16 @@ use ndarray::{ArrayBase, Data, Dimension};
 //     }
 // }
 
-impl<X, Y, A, S, D> Forward<X> for ArrayBase<S, D>
+impl<X, Y, A, S, D> Forward<X> for ArrayBase<S, D, A>
 where
     A: Clone,
     D: Dimension,
     S: Data<Elem = A>,
-    for<'a> X: Dot<ArrayBase<S, D>, Output = Y>,
+    for<'a> X: Dot<ArrayBase<S, D, A>, Output = Y>,
 {
     type Output = Y;
 
-    fn forward(&self, input: &X) -> crate::Result<Self::Output> {
-        let output = input.dot(self);
-        Ok(output)
+    fn forward(&self, input: &X) -> Option<Self::Output> {
+        Some(input.dot(self))
     }
 }
diff --git a/core/src/ops/reshape.rs b/traits/src/reshape.rs
similarity index 93%
rename from core/src/ops/reshape.rs
rename to traits/src/reshape.rs
index 61eb0db7..59021f2f 100644
--- a/core/src/ops/reshape.rs
+++ b/traits/src/reshape.rs
@@ -39,7 +39,7 @@ where
     }
 }
 
-impl<A, S, D> Unsqueeze for ArrayBase<S, D>
+impl<A, S, D> Unsqueeze for ArrayBase<S, D, A>
 where
     D: Dimension,
     S: RawData<Elem = A>,
@@ -51,7 +51,7 @@ where
     }
 }
 
-impl<A, S, D> Unsqueeze for &ArrayBase<S, D>
+impl<A, S, D> Unsqueeze for &ArrayBase<S, D, A>
 where
     D: Dimension,
     S: RawDataClone<Elem = A>,
diff --git a/core/src/traits/shape.rs b/traits/src/shape.rs
similarity index 100%
rename from core/src/traits/shape.rs
rename to traits/src/shape.rs
diff --git a/core/src/traits/store.rs b/traits/src/store.rs
similarity index 95%
rename from core/src/traits/store.rs
rename to traits/src/store.rs
index 0f8fd996..ccf11fc4 100644
--- a/core/src/traits/store.rs
+++ b/traits/src/store.rs
@@ -19,7 +19,7 @@ pub trait Sequential {
 
 macro_rules! impl_raw_store {
     (@impl $($name:ident)::*<$T:ident>) => {
-        impl<$T> $crate::traits::store::RawStore for $($name)::*<$T> {
+        impl<$T> $crate::store::RawStore for $($name)::*<$T> {
             type Elem = $T;
 
             seal!();
@@ -38,7 +38,7 @@ macro_rules! impl_raw_store {
 
 macro_rules! impl_sequential {
     (@impl $($name:ident)::*<$T:ident>) => {
-        impl<$T> $crate::traits::store::Sequential for $($name)::*<$T> {
+        impl<$T> $crate::store::Sequential for $($name)::*<$T> {
             seal!();
         }
     };
diff --git a/traits/src/tensor_ops.rs b/traits/src/tensor_ops.rs
new file mode 100644
index 00000000..e02aec70
--- /dev/null
+++ b/traits/src/tensor_ops.rs
@@ -0,0 +1,192 @@
+/*
+    appellation: tensor_ops <module>
+    authors: @FL03
+*/
+
+/// apply an affine transformation to a tensor;
+/// affine transformation is defined as `mul * self + add`
+pub trait Affine<X, Y = X> {
+    type Output;
+
+    fn affine(&self, mul: X, add: Y) -> Self::Output;
+}
+/// The [`Inverse`] trait generically establishes an interface for computing the inverse of a
+/// type, regardless of if its a tensor, scalar, or some other compatible type.
+pub trait Inverse {
+    /// the output, or result, of the inverse operation
+    type Output;
+    /// compute the inverse of the current object, producing some [`Output`](Inverse::Output)
+    fn inverse(&self) -> Self::Output;
+}
+/// The [`MatMul`] trait defines an interface for matrix multiplication.
+pub trait MatMul<Rhs = Self> {
+    type Output;
+
+    fn matmul(&self, rhs: &Rhs) -> Self::Output;
+}
+/// The [`MatPow`] trait defines an interface for computing the exponentiation of a matrix.
+pub trait MatPow<Rhs = Self> {
+    type Output;
+    /// raise the tensor to the power of the right-hand side, producing some [`Output`](Matpow::Output)
+    fn matpow(&self, rhs: Rhs) -> Self::Output;
+}
+
+/// The [`Transpose`] trait generically establishes an interface for transposing a type
+pub trait Transpose {
+    /// the output, or result, of the transposition
+    type Output;
+    /// transpose a reference to the current object
+    fn transpose(&self) -> Self::Output;
+}
+
+/*
+ ********* Implementations *********
+*/
+use ndarray::linalg::Dot;
+use ndarray::{Array, Array2, ArrayBase, Data, Dimension, Ix2, LinalgScalar, ScalarOperand, s};
+use num_traits::{Num, NumAssign};
+
+impl<A, D> Affine<A> for Array<A, D>
+where
+    A: LinalgScalar + ScalarOperand,
+    D: Dimension,
+{
+    type Output = Array<A, D>;
+
+    fn affine(&self, mul: A, add: A) -> Self::Output {
+        self * mul + add
+    }
+}
+
+// #[cfg(not(feature = "blas"))]
+impl<T> Inverse for Array<T, Ix2>
+where
+    T: Copy + NumAssign + ScalarOperand,
+{
+    type Output = Option<Self>;
+
+    fn inverse(&self) -> Self::Output {
+        let (rows, cols) = self.dim();
+
+        if !self.is_square() {
+            return None; // Matrix must be square for inversion
+        }
+
+        let identity = Array2::eye(rows);
+
+        // Construct an augmented matrix by concatenating the original matrix with an identity matrix
+        let mut aug = Array2::zeros((rows, 2 * cols));
+        aug.slice_mut(s![.., ..cols]).assign(self);
+        aug.slice_mut(s![.., cols..]).assign(&identity);
+
+        // Perform Gaussian elimination to reduce the left half to the identity matrix
+        for i in 0..rows {
+            let pivot = aug[[i, i]];
+
+            if pivot == T::zero() {
+                return None; // Matrix is singular
+            }
+
+            aug.slice_mut(s![i, ..]).mapv_inplace(|x| x / pivot);
+
+            for j in 0..rows {
+                if i != j {
+                    let am = aug.clone();
+                    let factor = aug[[j, i]];
+                    let rhs = am.slice(s![i, ..]);
+                    aug.slice_mut(s![j, ..])
+                        .zip_mut_with(&rhs, |x, &y| *x -= y * factor);
+                }
+            }
+        }
+
+        // Extract the inverted matrix from the augmented matrix
+        let inverted = aug.slice(s![.., cols..]);
+
+        Some(inverted.to_owned())
+    }
+}
+// #[cfg(feature = "blas")]
+// impl<T> Inverse for Array<T, Ix2>
+// where
+//     T: Copy + NumAssign + ScalarOperand,
+// {
+//     type Output = Option<Self>;
+
+//     fn inverse(&self) -> Self::Output {
+//         use ndarray_linalg::solve::Inverse;
+//         self.inv().ok()
+//     }
+// }
+
+impl<A, S, D, X, Y> MatMul<X> for ArrayBase<S, D, A>
+where
+    A: ndarray::LinalgScalar,
+    D: Dimension,
+    S: Data<Elem = A>,
+    ArrayBase<S, D, A>: Dot<X, Output = Y>,
+{
+    type Output = Y;
+
+    fn matmul(&self, rhs: &X) -> Self::Output {
+        <Self as Dot<X>>::dot(self, rhs)
+    }
+}
+
+impl<T> MatMul<Vec<T>> for Vec<T>
+where
+    T: Copy + Num,
+{
+    type Output = T;
+
+    fn matmul(&self, rhs: &Vec<T>) -> T {
+        self.iter()
+            .zip(rhs.iter())
+            .fold(T::zero(), |acc, (&a, &b)| acc + a * b)
+    }
+}
+
+impl<T, const N: usize> MatMul<[T; N]> for [T; N]
+where
+    T: Copy + Num,
+{
+    type Output = T;
+
+    fn matmul(&self, rhs: &[T; N]) -> T {
+        self.iter()
+            .zip(rhs.iter())
+            .fold(T::zero(), |acc, (&a, &b)| acc + a * b)
+    }
+}
+impl<A, S> MatPow<i32> for ArrayBase<S, ndarray::Ix2>
+where
+    A: Copy + Num + 'static,
+    S: Data<Elem = A>,
+    ArrayBase<S, Ix2>: Clone + Dot<ArrayBase<S, Ix2>, Output = Array<A, Ix2>>,
+{
+    type Output = Array<A, Ix2>;
+
+    fn matpow(&self, rhs: i32) -> Self::Output {
+        if !self.is_square() {
+            panic!("Matrix must be square to be raised to a power");
+        }
+        let mut res = Array::eye(self.shape()[0]);
+        for _ in 0..rhs {
+            res = res.dot(self);
+        }
+        res
+    }
+}
+
+impl<'a, A, S, D> Transpose for &'a ArrayBase<S, D, A>
+where
+    A: 'a,
+    D: Dimension,
+    S: Data<Elem = A>,
+{
+    type Output = ndarray::ArrayView<'a, A, D>;
+
+    fn transpose(&self) -> Self::Output {
+        self.t()
+    }
+}
diff --git a/core/src/traits/wnb.rs b/traits/src/wnb.rs
similarity index 61%
rename from core/src/traits/wnb.rs
rename to traits/src/wnb.rs
index ad586e4c..5e19f526 100644
--- a/core/src/traits/wnb.rs
+++ b/traits/src/wnb.rs
@@ -1,16 +1,16 @@
 use ndarray::{ArrayBase, Data, DataMut, Dimension, RawData};
 
-pub trait Weighted<S, D>
+pub trait Weighted<S, D, A = <S as RawData>::Elem>: Sized
 where
     D: Dimension,
-    S: RawData,
+    S: RawData<Elem = A>,
 {
     /// returns the weights of the model
-    fn weights(&self) -> &ArrayBase<S, D>;
+    fn weights(&self) -> &ArrayBase<S, D, A>;
     /// returns a mutable reference to the weights of the model
-    fn weights_mut(&mut self) -> &mut ArrayBase<S, D>;
+    fn weights_mut(&mut self) -> &mut ArrayBase<S, D, A>;
     /// assigns the given bias to the current weight
-    fn assign_weights(&mut self, weights: &ArrayBase<S, D>) -> &mut Self
+    fn assign_weights(&mut self, weights: &ArrayBase<S, D, A>) -> &mut Self
     where
         S: DataMut,
         S::Elem: Clone,
@@ -19,11 +19,11 @@ where
         self
     }
     /// replaces the current weights with the given weights
-    fn replace_weights(&mut self, weights: ArrayBase<S, D>) -> ArrayBase<S, D> {
+    fn replace_weights(&mut self, weights: ArrayBase<S, D, A>) -> ArrayBase<S, D, A> {
         core::mem::replace(self.weights_mut(), weights)
     }
     /// sets the weights of the model
-    fn set_weights(&mut self, weights: ArrayBase<S, D>) -> &mut Self {
+    fn set_weights(&mut self, weights: ArrayBase<S, D, A>) -> &mut Self {
         *self.weights_mut() = weights;
         self
     }
@@ -45,17 +45,17 @@ where
     }
 }
 
-pub trait Biased<S, D>: Weighted<S, D>
+pub trait Biased<S, D, A = <S as RawData>::Elem>: Weighted<S, D, A>
 where
     D: Dimension,
-    S: RawData,
+    S: RawData<Elem = A>,
 {
     /// returns the bias of the model
-    fn bias(&self) -> &ArrayBase<S, D::Smaller>;
+    fn bias(&self) -> &ArrayBase<S, D::Smaller, A>;
     /// returns a mutable reference to the bias of the model
-    fn bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller>;
+    fn bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller, A>;
     /// assigns the given bias to the current bias
-    fn assign_bias(&mut self, bias: &ArrayBase<S, D::Smaller>) -> &mut Self
+    fn assign_bias(&mut self, bias: &ArrayBase<S, D::Smaller, A>) -> &mut Self
     where
         S: DataMut,
         S::Elem: Clone,
@@ -64,11 +64,11 @@ where
         self
     }
     /// replaces the current bias with the given bias
-    fn replace_bias(&mut self, bias: ArrayBase<S, D::Smaller>) -> ArrayBase<S, D::Smaller> {
+    fn replace_bias(&mut self, bias: ArrayBase<S, D::Smaller, A>) -> ArrayBase<S, D::Smaller, A> {
         core::mem::replace(self.bias_mut(), bias)
     }
     /// sets the bias of the model
-    fn set_bias(&mut self, bias: ArrayBase<S, D::Smaller>) -> &mut Self {
+    fn set_bias(&mut self, bias: ArrayBase<S, D::Smaller, A>) -> &mut Self {
         *self.bias_mut() = bias;
         self
     }
@@ -93,32 +93,3 @@ where
 /*
  ************* Implementations *************
 */
-use crate::params::ParamsBase;
-
-impl<S, D> Weighted<S, D> for ParamsBase<S, D>
-where
-    S: RawData,
-    D: Dimension,
-{
-    fn weights(&self) -> &ArrayBase<S, D> {
-        &self.weights
-    }
-
-    fn weights_mut(&mut self) -> &mut ArrayBase<S, D> {
-        &mut self.weights
-    }
-}
-
-impl<S, D> Biased<S, D> for ParamsBase<S, D>
-where
-    S: RawData,
-    D: Dimension,
-{
-    fn bias(&self) -> &ArrayBase<S, D::Smaller> {
-        &self.bias
-    }
-
-    fn bias_mut(&mut self) -> &mut ArrayBase<S, D::Smaller> {
-        &mut self.bias
-    }
-}
diff --git a/traits/tests/default.rs b/traits/tests/default.rs
new file mode 100644
index 00000000..233a07af
--- /dev/null
+++ b/traits/tests/default.rs
@@ -0,0 +1,17 @@
+/*
+    Appellation: default <test>
+    Contrib: FL03 <jo3mccain@icloud.com>
+*/
+
+fn add<A, B, C>(a: A, b: B) -> C
+where
+    A: core::ops::Add<B, Output = C>,
+{
+    a + b
+}
+
+#[test]
+fn compiles() {
+    assert_eq!(add(10, 10), 20);
+    assert_ne!(add(1, 1), 3);
+}
diff --git a/traits/tests/traits.rs b/traits/tests/traits.rs
new file mode 100644
index 00000000..da2943a1
--- /dev/null
+++ b/traits/tests/traits.rs
@@ -0,0 +1,49 @@
+/*
+   Appellation: traits <test>
+   Contrib: FL03 <jo3mccain@icloud.com>
+*/
+use concision_traits::*;
+use ndarray::{Array2, array};
+
+#[test]
+fn test_affine() {
+    let x = array![[0.0, 1.0], [2.0, 3.0]];
+
+    let y = x.affine(4.0, -2.0);
+    assert_eq!(y, array![[-2.0, 2.0], [6.0, 10.0]]);
+}
+
+#[test]
+fn test_inverse() {
+    let a = array![[1.0, 2.0], [3.0, 4.0]];
+    let b = array![[1.0, 2.0, 3.0,], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]];
+    let exp = array![[-2.0, 1.0], [1.5, -0.5]];
+    assert_eq!(Some(exp), a.inverse());
+    assert_eq!(None, b.inverse());
+}
+
+#[test]
+fn test_masked_fill() {
+    let shape = (2, 2);
+    let mask = array![[true, false], [false, true]];
+    let arr = Array2::<f64>::from_shape_fn(shape, |(i, j)| (i * shape.1 + j) as f64);
+    let a = arr.masked_fill(&mask, 0.0);
+    assert_eq!(a, array![[0.0, 1.0], [2.0, 0.0]]);
+}
+
+#[test]
+fn test_matrix_power() {
+    let x = array![[1.0, 2.0], [3.0, 4.0]];
+    assert_eq!(x.matpow(0), Array2::<f64>::eye(2));
+    assert_eq!(x.matpow(1), x);
+    assert_eq!(x.matpow(2), x.dot(&x));
+}
+
+#[test]
+fn test_unsqueeze() {
+    let arr = array![1, 2, 3, 4];
+    let a = arr.clone().unsqueeze(0);
+    assert_eq!(a.dim(), (1, 4));
+    let b = arr.unsqueeze(1);
+    assert_eq!(b.dim(), (4, 1));
+}
diff --git a/utils/Cargo.toml b/utils/Cargo.toml
index 0fc27b00..1f237cbd 100644
--- a/utils/Cargo.toml
+++ b/utils/Cargo.toml
@@ -14,21 +14,8 @@ repository.workspace = true
 rust-version.workspace = true
 version.workspace = true
 
-[package.metadata.docs.rs]
-all-features = false
-features = ["full"]
-rustc-args = ["--cfg", "docsrs"]
-version = "v{{version}}"
-
-[package.metadata.release]
-no-dev-version = true
-tag-name = "{{version}}"
-
 [lib]
-crate-type = [
-    "cdylib", 
-    "rlib"
-]
+crate-type = ["cdylib", "rlib"]
 bench = false
 doc = true
 doctest = true
@@ -36,8 +23,7 @@ test = true
 
 [dependencies]
 # custom
-scsys = { workspace = true }
-scsys-derive = { workspace = true }
+variants = { workspace = true }
 # concurrency & parallelism
 rayon = { optional = true, workspace = true }
 # data & serialization
@@ -66,135 +52,108 @@ rand = { optional = true, workspace = true }
 rand_distr = { optional = true, workspace = true }
 
 [dev-dependencies]
+anyhow = { features = ["std"], workspace = true }
 lazy_static = { workspace = true }
 
-
 [features]
 default = [ 
-    "std",
+  "std",
 ]
 
 full = [
-    "anyhow",
-    "approx",
-    "complex",
-    "default",
-    "json",
-    "rand",
-    "serde",
-    "tracing",
+  "approx",
+  "complex",
+  "default",
+  "json",
+  "rand",
+  "serde",
+  "tracing",
 ]
 
 nightly = []
 
 # ************* [FF:Features] *************
 signal =[
-    "complex",
-    "rustfft",
+  "complex",
+  "rustfft",
 ]
 
 # ************* [FF:Dependencies] *************
 std = [
-    "alloc",
-    "anyhow?/std",
-    "ndarray/std",
-    "num/std",
-    "num-complex?/std",
-    "num-traits/std",
-    "rand?/std",
-    "rand?/std_rng",
-    "serde/std",
-    "scsys/std",
-    "strum/std",
-    "thiserror/std",
-    "tracing?/std",
-]
-
-wasi = [
-    "scsys/wasi",
-]
+  "alloc",
+  "ndarray/std",
+  "num/std",
+  "num-complex?/std",
+  "num-traits/std",
+  "rand?/std",
+  "rand?/std_rng",
+  "serde/std",
+  "strum/std",
+  "thiserror/std",
+  "tracing?/std",
+  "variants/std",
+]
+
+wasi = []
 
 wasm = [
-    "getrandom?/wasm_js",
-    "scsys/wasm",
+  "getrandom?/wasm_js",
 ]
 # ************* [FF:Dependencies] *************
 alloc = [
-    "num/alloc",
-    "serde?/alloc",
-    "serde_json?/alloc",
-    "scsys/alloc",
-]
-
-anyhow = [
-    "dep:anyhow",    
-    "scsys/anyhow",
+  "num/alloc",
+  "serde?/alloc",
+  "serde_json?/alloc",
+  "variants/alloc",
 ]
 
-approx = [
-    "dep:approx",
-    "ndarray/approx",
-]
+approx = ["dep:approx", "ndarray/approx"]
 
-blas = [
-    "ndarray/blas",
-]
+blas = ["ndarray/blas"]
 
 complex = ["dep:num-complex"]
 
 json = [
-    "alloc",
-    "scsys/json",
-    "serde",
-    "serde_json",
+  "alloc",
+  "serde",
+  "serde_json",
 ]
 
 rand = [
-    "dep:rand",
-    "dep:rand_distr",
-    "num/rand",
-    "num-complex?/rand",
-    "rng",
-    "scsys/rand",
+  "dep:rand",
+  "dep:rand_distr",
+  "num/rand",
+  "num-complex?/rand",
+  "rng",
 ]
 
-rayon = [
-    "dep:rayon",
-    "ndarray/rayon",
-]
+rayon = ["dep:rayon", "ndarray/rayon"]
 
 rng = [
-    "dep:getrandom",
-    "rand?/small_rng",
-    "rand?/thread_rng",
-    "scsys/rng",
+  "dep:getrandom",
+  "rand?/small_rng",
+  "rand?/thread_rng",
 ]
 
 rustfft = ["dep:rustfft"]
 
 serde = [
-    "dep:serde",
-    "dep:serde_derive",
-    "ndarray/serde",
-    "num/serde",
-    "num-complex?/serde",
-    "rand?/serde",
-    "rand_distr?/serde",
-    "scsys/serde",
+  "dep:serde",
+  "dep:serde_derive",
+  "ndarray/serde",
+  "num/serde",
+  "num-complex?/serde",
+  "rand?/serde",
+  "rand_distr?/serde",
 ]
 
 serde_json = ["dep:serde_json"]
 
-tracing = [
-    "dep:tracing",
-    "scsys/tracing",
-]
-
+tracing = ["dep:tracing"]
 
-# ************* [Unit Tests] *************
+# ********* [Unit Tests] *********
 [[test]]
 name = "default"
-required-features = []
 
 [[test]]
 name = "fft"
@@ -207,3 +166,14 @@ required-features = ["approx", "std", "complex"]
 [[test]]
 name = "traits"
 required-features = ["approx", "std", "complex"]
+
+# ********* [Metadata] *********
+[package.metadata.docs.rs]
+all-features = false
+features = ["full"]
+rustc-args = ["--cfg", "docsrs"]
+version = "v{{version}}"
+
+[package.metadata.release]
+no-dev-version = true
+tag-name = "{{version}}"
\ No newline at end of file
diff --git a/utils/src/signal/fft/types/mode.rs b/utils/src/signal/fft/types/mode.rs
index 20f1efe5..89c97059 100644
--- a/utils/src/signal/fft/types/mode.rs
+++ b/utils/src/signal/fft/types/mode.rs
@@ -52,7 +52,6 @@ toggle! {
     Ord,
     PartialEq,
     PartialOrd,
-    scsys::VariantConstructors,
     strum::AsRefStr,
     strum::Display,
     strum::EnumCount,
@@ -61,6 +60,7 @@ toggle! {
     strum::EnumString,
     strum::VariantArray,
     strum::VariantNames,
+    variants::VariantConstructors,
 )]
 #[cfg_attr(
     feature = "serde",
@@ -85,7 +85,6 @@ pub enum FftMode {
     Ord,
     PartialEq,
     PartialOrd,
-    scsys::VariantConstructors,
     strum::AsRefStr,
     strum::Display,
     strum::EnumCount,
@@ -94,6 +93,7 @@ pub enum FftMode {
     strum::EnumString,
     strum::VariantArray,
     strum::VariantNames,
+    variants::VariantConstructors,
 )]
 #[cfg_attr(
     feature = "serde",
diff --git a/utils/src/signal/fft/types/plan.rs b/utils/src/signal/fft/types/plan.rs
index fc54da79..997c3ed8 100644
--- a/utils/src/signal/fft/types/plan.rs
+++ b/utils/src/signal/fft/types/plan.rs
@@ -2,15 +2,13 @@
    Appellation: plan <mod>
    Contrib: FL03 <jo3mccain@icloud.com>
 */
-use core::slice;
-
 use crate::signal::fft::fft_permutation;
 
+#[cfg(feature = "alloc")]
+use alloc::vec::{self, Vec};
+
 #[derive(Clone, Debug, Default, Eq, Hash, Ord, PartialEq, PartialOrd)]
-#[cfg_attr(
-    feature = "serde",
-    derive(serde_derive::Deserialize, serde_derive::Serialize)
-)]
+#[cfg_attr(feature = "serde", derive(serde::Deserialize, serde::Serialize))]
 pub struct FftPlan {
     len: usize,
     plan: Vec<usize>,
@@ -38,7 +36,7 @@ impl FftPlan {
         self.plan().get(index)
     }
 
-    pub fn iter(&self) -> slice::Iter<usize> {
+    pub fn iter<'a>(&'a self) -> core::slice::Iter<'a, usize> {
         self.plan().iter()
     }
 
@@ -93,7 +91,7 @@ impl FromIterator<usize> for FftPlan {
 
 impl IntoIterator for FftPlan {
     type Item = usize;
-    type IntoIter = std::vec::IntoIter<Self::Item>;
+    type IntoIter = vec::IntoIter<Self::Item>;
 
     fn into_iter(self) -> Self::IntoIter {
         self.plan.into_iter()
@@ -102,7 +100,7 @@ impl IntoIterator for FftPlan {
 
 impl<'a> IntoIterator for &'a mut FftPlan {
     type Item = &'a mut usize;
-    type IntoIter = slice::IterMut<'a, usize>;
+    type IntoIter = core::slice::IterMut<'a, usize>;
 
     fn into_iter(self) -> Self::IntoIter {
         self.plan.iter_mut()
diff --git a/utils/src/stats/summary.rs b/utils/src/stats/summary.rs
index 2e148653..5be21462 100644
--- a/utils/src/stats/summary.rs
+++ b/utils/src/stats/summary.rs
@@ -147,13 +147,13 @@ where
     }
 
     fn std(&self) -> Self::Output {
-        let mean = self.mean().unwrap_or_else(A::zero);
+        let mean = self.mean();
         let sum = self.iter().copied().map(|x| (x - mean).pow(2)).sum::<A>();
         (sum / self.elems()).sqrt()
     }
 
     fn var(&self) -> Self::Output {
-        let mean = self.mean().unwrap_or_else(A::zero);
+        let mean = self.mean();
         let sum = self.iter().copied().map(|x| (x - mean).pow(2)).sum::<A>();
         sum / self.elems()
     }