Regenera Ledger: AI-Powered ESG Intelligence & Carbon Transparency

An end-to-end platform for automated ESG forensic auditing, Scope 3 supply chain reasoning, and Company-to-Farmer carbon credit matching. Powered by Google Gemini 2.0 and Firebase.

🌟 Key Features

• Forensic ESG Auditor: Upload ESG reports (PDF) to detect greenwashing, verify reported emissions vs. detected risk, and uncover "red flags."
• Scope 3 Whistleblower: Cross-reference shipping manifests with corporate reports to identify undisclosed supply chain emissions.
• Carbon Gap Analysis: Real-time calculation of the "Carbon Gap" between corporate claims and data-driven estimates.
• Regenerative Farmer Marketplace: Match carbon-heavy companies with verified regenerative farmers for direct carbon sequestration projects.
• AI Farmer Estimation: Leverages Gemini to estimate sequestration capacity based on soil, crop, and location data.
• Full Audit Logging: Every sensitive action is logged for compliance and forensic accountability.

🏗 Tech Stack

• Frontend: React (Vite), Chart.js, Leaflet (Maps), Axios.
• Backend: Python (FastAPI), Pydantic.
• Intelligence Engine: Google Gemini 2.0 (via google-genai).
• Data Processing: PDFMiner, Pandas, Custom T2 Bridge modules.
• Database & Auth: Firebase Firestore + JWT (PyJWT).

📁 Project Structure

GEMINATHON/
├── backend/            # FastAPI Backend
│   ├── ai/             # Gemini API Client
│   ├── data/           # PDF/Manifest parsers & processing logic
│   ├── middleware/     # Auth & Error handlers
│   ├── prompts/        # Gemini prompt engineering templates
│   ├── routes/         # API Endpoints (ESG, Farmer, Matching, etc.)
│   └── utils/          # File upload & Audit logging
├── frontend/           # React Frontend (Vite)
├── database/           # Firestore schema & security rules
└── README.md           # You are here!

🚀 Getting Started

1. Prerequisites

• Python 3.10+
• Node.js 18+
• Google Gemini API Key (AI Studio)
• Firebase Service Account Key (Firebase Console)

2. Backend Setup

1. Navigate to the backend folder:

   cd backend

2. Install dependencies:

   pip install -r requirements.txt

3. Place your firebase-service-account.json in the backend/ directory.
4. Create a .env file (refer to .env.example) and add your keys:

   GEMINI_API_KEY=your_key_here
   JWT_SECRET=some_random_secret

5. Seed the database with demo data:

   python seed.py

6. Start the server:

   uvicorn main:app --reload

3. Frontend Setup

1. Navigate to the frontend folder:

   cd frontend

2. Install dependencies:

   npm install

3. Start the dev server:

   npm run dev

👥 Builders

• Suneev Kundu: AI/Backend
• Shaun Joseph: Data/Matching Logic
• Ayaan Saju: Frontend
• Tanmay Nair: DevOps

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.