The ABARE (AI-Based Analysis of Real Estate) Platform v2 is an enterprise-grade commercial real estate intelligence platform that combines AI-powered document processing with institutional-grade financial analysis. This platform helps CRE brokers, investors, and lenders make better-informed decisions by automating document analysis and providing deep insights into property performance.
- AI Document Processing: Automatically extract key data from rent rolls, P&Ls, and leases
- Financial Analysis Engine: Comprehensive deal metrics (NOI, Cap Rate, DSCR, IRR)
- Intelligent Dashboard: Modern, intuitive interface with real-time monitoring
- Market Intelligence: Treasury rates and SOFR spreads integration
- FastAPI: Modern, high-performance web framework
- MongoDB: NoSQL database (with in-memory fallback option)
- PyJWT: JSON Web Token for authentication
- Pydantic: Data validation and settings management
- Motor: Async MongoDB driver
- PyPDF2: PDF processing library
- Next.js: React framework with SSR capabilities
- Mantine UI: Component library with dark mode support
- TypeScript: Type-safe JavaScript
- Axios: HTTP client for API requests
- React Query: Data fetching and state management
- Recharts: Composable charting library
- React Hook Form: Form validation
- Node.js (v18.0.0 or higher)
- Python (v3.10 or higher)
- MongoDB (v5.0 or higher)
# Navigate to the frontend directory
cd frontend
# Install dependencies
npm install
# Create a .env.local file
cp .env.local.example .env.local
# Start the development server
npm run dev
# Navigate to the backend directory
cd backend
# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # On Windows, use: venv\Scripts\activate
# Install dependencies
pip install -r ../requirements.txt
# Start the FastAPI server
uvicorn app.main:app --reload
The project follows a modular architecture with separate frontend and backend codebases:
abare-v2/
├── backend/ # FastAPI backend
│ ├── app/ # Application code
│ │ ├── api/ # API endpoints
│ │ ├── models/ # MongoDB models
│ │ ├── schemas/ # Pydantic schemas
│ │ ├── services/ # Business logic
│ │ └── db/ # Database connections
│ ├── tests/ # Backend tests
│ └── static/ # Static files
│
└── frontend/ # Next.js frontend
├── public/ # Static assets
└── src/ # Source code
├── components/ # React components
├── pages/ # Next.js pages
├── services/ # API client services
├── hooks/ # Custom React hooks
├── context/ # React contexts
├── utils/ # Utility functions
└── styles/ # CSS and styling
- Secure user authentication with JWT
- Role-based access control
- Add, edit, and view commercial real estate properties
- Track property metrics and performance
- Upload and process various commercial real estate documents
- AI-powered data extraction from PDFs
- Generate comprehensive financial analyses
- Visualize key metrics with interactive charts
cd backend
pytest
cd frontend
npm test
cd backend
flake8
cd frontend
npm run lint
cd frontend
npm run build
For production, it's recommended to use Gunicorn with Uvicorn workers:
cd backend
gunicorn -w 4 -k uvicorn.workers.UvicornWorker app.main:app
Docker support is coming soon.
When the backend server is running, interactive API documentation is available at:
- Swagger UI:
http://localhost:8000/docs
- ReDoc:
http://localhost:8000/redoc
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add some amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- This project is the successor to the original ABARE platform
- Built with modern, open-source technologies
- Developed for the commercial real estate industry
This project is currently under active development. The frontend structure is in place, and we are now working on implementing the backend authentication API.