Fast, typed Python APIs with FastAPI.
Hire senior engineers to build your FastAPI service and host it on AWS. Async endpoints, clean contracts, and a PostgreSQL data layer that holds up under load, written by the people you talk to.
Async
Non-blocking endpoints that handle concurrency well
Typed
Pydantic validation and self-documenting OpenAPI specs
Lean
Small, fast services that are cheap to run on AWS
What we build with FastAPI
FastAPI is our default when speed and clean APIs matter. Here is where it fits best.
Product and REST APIs
The API your web and mobile clients talk to, designed with clear contracts and versioning.
AI and LLM backends
The service layer behind AI features, retrieval, and agents, where async really pays off.
Microservices
Small, independent services that scale on their own and stay easy to reason about.
Real-time and data
Streaming endpoints, webhooks, and data pipelines that move information as it happens.
Built to stay quick under real load
Speed on a benchmark means little if the database is the bottleneck. We pair FastAPI with async SQLAlchemy and proper connection pooling, keep slow work in background tasks, and cache with Redis where it earns its place. Deployed on ECS Fargate with uvicorn workers and CI/CD pipelines, the service stays responsive as traffic climbs.
- Async SQLAlchemy with connection pooling
- Background tasks off the request path
- Redis caching where it helps
FastAPI or Django?
Not sure which fits? Here is the short version. We will give you a straight recommendation on the call.
Reach for FastAPI when
- You need a high-throughput async API or microservice
- You are building backends for AI, data, or real-time
- You want a lean service that is cheap to run
Reach for Django when
- You want a full framework with a built-in admin
- The product is content or workflow heavy
- You value batteries-included conventions
FastAPI on AWS questions
FastAPI shines for high-throughput async APIs, microservices, and AI or data backends. Django suits content-heavy, admin-driven products. We help you pick, and often run them together with FastAPI as a service layer alongside Django.
We package the service with Docker and run it on ECS Fargate behind gunicorn with uvicorn workers, released through CI/CD pipelines and defined as infrastructure as code so it is repeatable.
Yes. We use async SQLAlchemy with connection pooling, keep heavy work off the request path, and add caching with Redis, so the API stays responsive as load grows.
That is a common request. FastAPI is well suited to AI workloads, and we build the endpoints behind LLM features, retrieval, and automation as part of our AI integration work.
Either. You can bring on a single senior Python developer by the hour or a full squad on a monthly plan. We suggest the right shape for what you are building rather than overselling a team.
Yes. We can keep maintaining and extending the API after it ships, with security updates, new endpoints, and scaling as traffic grows. We agree what that support looks like with you.
Most projects start with a free 30-minute scoping call where we agree the scope and a realistic timeline. Reach us through the contact form or at info@shapeincloud.com.
Let's build, scale, or automate it.
Hire a full senior team or a single specialist across frontend, backend, AWS, DevOps, and AI. You work directly with the engineers, not an account manager.