This is complete, production-ready source code for an AI-powered expense management software. You receive the full codebase—backend, frontend, and trained AI/ML models—to deploy, customize, and build upon for your own business or clients.
The system uses computer vision and OCR to scan receipts and automatically extract transaction data. Machine learning models categorize expenses with 85%+ accuracy using ensemble classification, detect fraudulent or unusual spending patterns through isolation forest algorithms, and provide budget forecasts via time-series analysis. Users can query their expenses in plain English, view interactive dashboards with category breakdowns, and manage multi-level approval workflows across multiple currencies.
Built with Python FastAPI on the backend and React TypeScript on the frontend, the application includes JWT authentication, role-based access control, Redis caching, and Docker Compose deployment configurations. AI capabilities are implemented natively—not API wrappers—using scikit-learn, TensorFlow, OpenCV, and Tesseract OCR. The system includes a synthetic data generator that creates training examples to improve model coverage while protecting user privacy.
Technical stack: Python 3.10+, FastAPI, SQLAlchemy, PostgreSQL/SQLite, React 18, TypeScript, Tailwind CSS, and standard ML libraries. Includes comprehensive documentation: README with feature overview, API documentation with endpoint reference, and installation guide. Total codebase: 7,102 lines across 69 files.
Ideal for developers, agencies, or entrepreneurs who want to launch their own expense management SaaS, add expense tracking to existing products, or offer customized solutions to clients without building from scratch.
