🚀 AI-Driven Performance Marketing SaaS
An intelligent SaaS platform to analyze competitor strategies and generate high-performing ad campaigns using generative AI.
This project was built for the GDGVITM Hackbuild 2.0 Hackathon.
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📜 About The Project Marketers spend millions on digital ads but often struggle to create effective campaigns due to a lack of insight into competitor strategies and market trends. While ad transparency APIs exist, businesses lack a single, intelligent system to collect, analyze, and act on this competitive intelligence, leading to wasted ad spend and missed opportunities.
This platform leverages AI to provide deep competitor analytics and automates the creative process, helping businesses maximize their return on investment (ROI).
Built With This project is powered by a modern, scalable tech stack:
📋 Table of Contents ✨ Core Features
🛠 Technology Stack
🏗 Project Architecture
⚙️ Getting Started
Prerequisites
Installation
🏆 Hackathon
✨ Core Features Live Competitor Discovery: Describe your product to discover active competitors via the Meta Ad Library API.
Competitor Ad Feed: View a real-time feed of competitor ads to understand their current strategies.
AI-Powered Text Analysis: Automatically analyze ad copy for tone (e.g., Urgent, Inspirational) using Hugging Face NLP.
Interactive AI Strategy Simulator: Generate unique headlines, body copy, and image prompts with Groq's Llama 3 based on your creative direction.
Explainable AI (XAI): Understand the why behind the AI's strategic recommendations to build trust and marketing knowledge.
Simulated Real-Time Alerts: Get notified of new competitor ad campaigns as they launch.
🛠 Technology Stack Here's a detailed breakdown of the technologies used in this project.
Category
Technology
Backend
Python, FastAPI, Uvicorn
Frontend
React.js, Plain CSS
AI/ML
Groq API (Llama 3), Hugging Face Transformers
Live Data
Meta (Facebook) Ad Library API
🏗 Project Architecture The backend is built on a scalable, modular "Universal Adapter" pattern. Each ad platform (Meta, Google) has its own connector responsible for fetching data and translating it into a standardized internal format (StandardAd). This keeps the core logic clean and makes it easy to add new data sources without major refactoring.
⚙️ Getting Started To get a local copy up and running, follow these simple steps.
Prerequisites Ensure you have the following installed on your system:
Git
Python 3.10+
Node.js v18+ and npm
Installation Clone the Repository
git clone https://github.com/GDGVITM/hackbuild-Invictus.git cd hackbuild-Invictus
Backend Setup
cd backend
python -m venv venv source venv/bin/activate # On Windows, use: venv\Scripts\activate
cp .env.example .env
Now, open the .env file and add your API keys:
GROQ_API_KEY="your_groq_api_key" META_ACCESS_TOKEN="your_meta_access_token"
Frontend Setup
cd frontend-react
npm install
Running the Application You will need two terminals open simultaneously.
Terminal 1 (Backend):
cd backend source venv/bin/activate uvicorn main:app --reload
Terminal 2 (Frontend):
cd frontend-react npm start
Finally, open your browser to http://localhost:3000.
🏆 Hackathon This project was developed for the GDGVITM Hackbuild 2.0 Hackathon.