FastAPI Development Companies: Top 12 Agencies (2025)

FastAPI is the fastest-growing Python framework in 2025, with 38% adoption (up from 29%) and 9+ million monthly PyPI downloads—now surpassing Django. If you're building high-performance APIs, microservices, or ML model endpoints, here's how to find agencies with real FastAPI expertise.

Top 12 FastAPI Development Companies

These agencies have proven FastAPI experience through portfolio projects, technical interviews, and client references. Ranked by API/microservices expertise, async Python knowledge, and delivery track record.

Need to see full company profiles with client references? View all 30 Python development companies with complete scoring methodology.

FastAPI vs Django vs Flask: Decision Framework

Quick answer: FastAPI excels at pure API development with maximum performance. Django is better for full-stack web applications. Flask sits in the middle with maximum flexibility.

Choose FastAPI When:

• Building pure APIs - REST, GraphQL, or gRPC endpoints without server-rendered HTML
• Performance is critical - High-throughput services handling thousands of concurrent requests
• Microservices architecture - Small, focused services that need to be fast and independent
• ML model serving - Inference APIs where async operations reduce latency
• Type safety matters - Teams that value compile-time error catching via type hints
• Auto-documentation required - When OpenAPI/Swagger docs must stay in sync automatically
• Real-time features - WebSocket heavy applications (chat, live updates, streaming)

Choose Django Instead When:

• Full web application - Server-rendered pages, forms, user authentication, sessions
• Admin panel needed - Internal tools where Django's admin saves weeks of work
• Content management - CMS, blogs, e-commerce with complex content models
• Rapid prototyping - Need full-stack MVP in 4-6 weeks with all features
• Team familiarity - Your developers know Django but not async Python

Looking for Django specialists? Compare 18 Django development companies.

FastAPI Project Cost Estimates

For detailed pricing across all Python project types, see our complete cost breakdown guide with 240 real quotes analyzed.

How to Vet FastAPI Expertise

FastAPI is newer (2018), so many "Python agencies" lack real FastAPI experience. Here's how to verify actual expertise:

Technical Questions to Ask

1. "Show me a production FastAPI project with 100+ RPS"
   Why: Tests if they've handled real scale, not just tutorials
2. "How do you handle database connection pooling in async FastAPI?"
   Good answer: Should mention SQLAlchemy async, connection pool limits, or databases library
3. "What's your strategy for testing async endpoints?"
   Good answer: pytest-asyncio, httpx.AsyncClient, not requests
4. "How do you structure a FastAPI project with 50+ endpoints?"
   Good answer: Routers, dependency injection, layered architecture, not one giant main.py
5. "Explain Pydantic v2 performance improvements"
   Why: Tests if they keep up with ecosystem changes (Pydantic v2 is 5-50x faster)
6. "How do you handle background tasks vs Celery in FastAPI?"
   Good answer: Built-in BackgroundTasks for simple jobs, Celery/ARQ for heavy work
7. "What ASGI server do you deploy with and why?"
   Good answer: Uvicorn with Gunicorn workers, or Hypercorn with reasoning

Portfolio Red Flags

• "We use FastAPI for everything" - Should recommend Django when appropriate
• No production FastAPI projects - Only personal projects or tutorials
• Can't explain async/await tradeoffs - Don't understand event loop blocking
• Using requests library in async code - Shows lack of async knowledge
• No mention of Pydantic - Core to FastAPI, can't miss it
• Sync database drivers in async app - Performance anti-pattern

Reality check: FastAPI expertise is rarer than Django expertise. If an agency claims both equally, probe deeper on FastAPI. Most Django shops are adding FastAPI to their marketing but lack deep async Python experience.

FastAPI Architecture Patterns

Pattern 1: API Gateway + Microservices

When: Multiple services need unified entry point
Setup: FastAPI gateway routes to internal services
Benefit: Central authentication, rate limiting, monitoring
Cost impact: +20-30% for gateway layer

Pattern 2: Event-Driven with Message Queues

When: Decoupled services, async processing
Setup: FastAPI + RabbitMQ/Kafka
Benefit: Scalability, fault tolerance
Cost impact: +40-50% for message infrastructure

Pattern 3: Serverless FastAPI

When: Variable traffic, cost optimization
Setup: Mangum adapter + AWS Lambda/GCP Functions
Benefit: Pay-per-request, auto-scaling
Cost impact: Lower infra cost, higher development complexity

Common FastAPI Project Mistakes

FastAPI Development Timeline