What is Studzee?

Studzee is a full-stack SaaS educational platform designed to transform how educational content is created, structured, delivered, and consumed across multiple platforms.

It unifies content ingestion, intelligent processing, secure delivery, and real-time engagement into a single ecosystem. Studzee supports document-based learning at scale while laying the foundation for AI-driven automation, enabling both manual and fully autonomous content workflows.

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Who Is Studzee For?

Studzee is built for multiple stakeholders within the learning ecosystem:

• Students & Learners Consume structured educational content, summaries, and quizzes across mobile, web, and desktop platforms.

• Educators & Content Creators Upload documents, curate learning material, and manage structured educational resources.

• Administrators Oversee content pipelines, approval workflows, notifications, and platform-wide operations through a dedicated control panel.

• Developers & Contributors Work with a modular, microservice-oriented architecture designed for scalability, observability, and long-term evolution.

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High-Level Architecture & System Flow

Studzee follows a distributed, service-oriented architecture with clear separation of concerns.

System Flow Overview

1. Client Applications (Mobile, Website, Desktop) interact with the Backend API.

2. Backend (API) handles:

   • Authentication & authorization
   • Content management
   • Caching and persistence
   • Orchestration of downstream services

3. Notification Service operates asynchronously:

   • Push notifications (Expo)
   • Transactional emails

4. Storage & Caching Layers

   • MongoDB / PostgreSQL for persistence
   • Redis for high-performance caching
   • Object storage for uploaded assets

5. Future AI & Processing Services

   • Content validation
   • Structuring
   • Quiz & summary generation
   • External data ingestion (PDFs, web sources)

Each service is independently deployable, enabling fault isolation, horizontal scaling, and controlled rollouts.

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Service Responsibilities & Boundaries

Clear responsibility boundaries ensure maintainability and scalability.

BACKEND (API)

• Core business logic
• Content lifecycle management
• Caching strategy and orchestration
• Secure authentication via Clerk
• Integration point for AI and processing services

NOTIFICATION Service

• Push notification delivery
• Transactional email handling
• Event-driven communication only
• No business logic or data ownership

CLIENT APPLICATIONS

• Mobile, Web, and Desktop clients
• Content consumption and interaction
• Platform-specific UI/UX
• Authentication handled centrally via Backend

Future SERVICE Layer (Planned)

• Dedicated services for:

  • PDF text extraction
  • Web scraping
  • Additional ingestion pipelines

• Designed to be isolated, retryable, and failure-resilient

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Expanded Roadmap: Agentic AI System

Current State: Content is manually uploaded and structured by administrators.

Planned Agentic AI Capabilities

The upcoming Agentic AI system will be responsible for content intelligence and automation, including:

• Content validation and structuring
• Automatic quiz generation
• Intelligent summaries
• Metadata enrichment and categorization

AI Workflows

The AI system will operate through two primary workflows:

1. PDF-Based Workflow

• Accepts large batches of PDFs (200+)
• Extracts raw text using a dedicated extraction service
• Analyzes extracted content
• Structures learning material
• Generates summaries and quizzes

2. Web-Based Workflow

• Accepts external links
• Scrapes relevant educational content
• Processes and structures extracted data
• Generates learning artifacts (content, quizzes, summaries)

Service-First Design

• PDF extraction and web scraping will live in separate services

• Enables:

  • Independent scaling
  • Fault isolation
  • Easier recovery and retries

• Additional ingestion services can be added without impacting core systems

All AI logic will reside in the upcoming Agent folder.

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Deployment Strategy & Infrastructure Panels

Studzee supports two distinct deployment panels, designed for flexibility and cost optimization.

Panel 1: Free / Community Deployment

Used for testing, development, and early access environments.

• Render
• MongoDB Atlas
• Neon PostgreSQL
• Managed Redis providers
• Docker-based deployments

This panel prioritizes cost efficiency and rapid iteration.

Panel 2: Production-Grade AWS Deployment

A fully managed, enterprise-ready infrastructure built on AWS:

• Terraform-based infrastructure pipelines
• Load balancing and auto-scaling
• Secure networking and isolation
• Domain configuration via Route 53
• High availability and observability

This panel is optimized for performance, reliability, and scale.

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Website & Public Access

• 🌐 Official Website: https://studzee.in
• Domain management and DNS are handled through AWS Route 53 for production deployments.

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Minor Documentation Notes

• Folder VERSION and BRANCH values are tied to automated deployment workflows.
• Production pushes trigger redeployment of all listed services.
• Always validate changes locally before pushing to production branches.

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Testing, Containerization & Local Orchestration

All Studzee services are designed with production-readiness as a first-class concern.

Testing Strategy

Each service includes:

• Unit and integration testing
• Environment-specific configurations
• Automated test execution in CI pipelines

Testing ensures service stability, contract safety, and confidence during deployments.

Containerization

• Every service is packaged as an independent Docker image

• Dockerfiles are optimized for:

  • Reproducible builds
  • Minimal runtime footprint
  • Clear separation between build and runtime stages

Local Development & Orchestration

• Docker Compose is used for:

  • Local service orchestration
  • End-to-end testing
  • Simulating production-like environments

• Developers can run the entire ecosystem locally without external dependencies.

This approach enables fast iteration while maintaining parity with production environments.

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Future Infrastructure: Kubernetes & AWS (EKS)

Once the core Studzee platform is fully stabilized, all services will transition to a unified cloud-native deployment model.

Kubernetes-Based Architecture

• All services will be deployed as containers in AWS Elastic Kubernetes Service (EKS)

• Kubernetes will handle:

  • Service discovery
  • Horizontal scaling
  • Rolling updates
  • Fault tolerance and self-healing

Complete Docker Orchestration

Studzee will operate as a fully container-orchestrated application, where:

• Each microservice is independently deployable
• Failures are isolated
• Scaling policies are service-specific
• Infrastructure changes are managed declaratively

This evolution ensures long-term scalability, resilience, and operational clarity.

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Mobile Application Status

Android Application (v1)

• The first version of the Studzee Android app is nearing completion

• 📱 Planned Release: Google Play Store (v1)

• The initial release will focus on:

  • Content consumption
  • Notifications
  • Core learning workflows

Future releases will incrementally introduce advanced features as the platform evolves.

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Why This Matters

These design decisions ensure that Studzee:

• Scales seamlessly from development to production
• Maintains strong reliability guarantees
• Supports rapid experimentation without compromising stability
• Is future-proofed for enterprise-grade deployments