What it is
I build FastAPI backends designed specifically for LLM-powered applications in production. Async endpoints built for streaming responses, proper authentication and API key management, per-user rate limiting, request and response logging, cost tracking, and error handling that doesn’t let a bad model response take down the whole service. Production infrastructure — not a script someone will have to babysit when traffic picks up.
Who it's for
Teams who’ve built an AI prototype and need a backend that can actually serve it to real users at scale. SaaS products that need a scalable AI layer with multi-tenant support and usage controls. Anyone who’s running LLM calls directly from the frontend and knows that needs to change.
What you get
- FastAPI backend with async LLM endpoints and full streaming support
- Auth layer (API keys, JWT, or OAuth depending on your setup)
- Rate limiting and usage quotas configurable per user or pricing tier
- Centralized prompt management and version tracking
- Request logging, cost tracking, and error monitoring built in
- Typical result: AI feature ready to handle real user load with full observability from day one
Common questions
Python is where the AI ecosystem lives — the best LLM clients, embedding tools, and inference libraries are all Python-first. FastAPI gives you async performance, automatic API documentation, and type safety that makes the backend maintainable over time, not just functional on launch day.