The AI/ML stack we ship to clients in 2026

After shipping 20+ AI/ML projects, we have settled on a tech stack that balances speed, scalability, and maintainability. **Backend: Python + FastAPI** FastAPI is 3x faster than Flask and comes with automatic OpenAPI docs. Perfect for serving ML models as REST APIs. **Models: Hugging Face + Scikit-learn** Hugging Face gives us state-of-the-art NLP models. Scikit-learn handles traditional ML like regression and classification. **Frontend: React (lightweight)** We use a minimal React setup — no Next.js or complex state management. Just a form, a results display, and a chart. **Deployment: Render / Railway** Both offer free tiers and support Python natively. We use Docker for reproducibility. **Database: MongoDB** Flexible schema handles the varied data structures ML projects generate. This stack has shipped everything from sentiment analysis dashboards to medical image classifiers. It works, it is fast, and clients love it.