AI Inference Engine
Serving thousands of ML inferences per second using FastAPI backend.
APIs That Handle Millions of Requests. Built to Last Forever.
Leverage the speed, asynchronous capabilities, and raw computing power of FastAPI. We build high-performance APIs for web and mobile ecosystem.
Fastapi powers production at
The API Framework That Powers The Modern Web Architecture.
The parts of Fastapi we rely on for production builds.
High Performance
On par with NodeJS and Go.
Python Type Hints
For reduced bugs in production.
Native Async
Handle thousands of concurrent users.
OpenAPI Specs
Automatic documentation rendering.
Fastapi works best when the architecture matches the product constraints.
Is Fastapi right for your project?
Here is when we recommend Fastapi, and when we recommend a different path.
FastAPI fits if
Build highly concurrent chat and streaming apps.
Serve Machine Learning models at scale with Python.
Develop lightning fast microservices.
Have native OpenAPI documentation.
Consider alternatives if
Simple monolithic apps with low traffic.
CMS websites without heavy backend logic.
Projects mostly using synchronous Python.
We will recommend the simpler path when it is the better fit.
What a proper Fastapi build delivers
Production outcomes we focus on during Fastapi engagements.
Our API blocks under real load and we're scaling servers just to keep response times acceptable.
Native async support that handles real scale
Designed natively for async/await allowing you to handle thousands of requests seamlessly without blocking threads.
Every endpoint has hand-written validation code that nobody keeps in sync with the actual contracts.
Automatic data validation with zero boilerplate
Validates data using Pydantic instantly under the hood. No more writing tedious request-body validation code.
Our API documentation is always stale by the time a client or new engineer reads it.
Built-in Swagger docs generated from your code
Automatically generated interactive API documentation (Swagger UI/ReDoc) directly from your code.
Our service needs extra glue scripts to fit into our container and CI/CD setup.
Cloud-native architecture that deploys anywhere
FastAPI integrates seamlessly into modern DevOps flows, running efficiently in small, stateless containers.
Comparison table
A practical comparison based on product fit, delivery speed, and long-term ownership.
Performance
FastAPI
Very High
Django
Moderate
Flask
Moderate
Node.js
High
Async Support
FastAPI
Native
Django
Added Recently
Flask
Plugins needed
Node.js
Native
Typing & Validation
FastAPI
Pydantic Integrated
Django
External libraries
Flask
External libraries
Node.js
TypeScript compatible
Auto Documentation
FastAPI
Swagger/ReDoc Built-in
Django
Requires config
Flask
Requires config
Node.js
Requires packages
Fastapi projects we have shipped
Representative project patterns and outcomes.
View Project
Trading Data API
High-frequency asynchronous WebSockets serving real-time crypto prices.
SaaS Backend Layer
A decoupled microservice architecture powering a global CRM platform.
Problem / Solution
Common Fastapi problems and how we solve them.
High Latency in ML APIs: Heavy data processing blocks traditional synchronous frameworks, increasing response times.
Asynchronous Processing: We leverage Python's asyncio to process ML tasks without blocking API requests natively.
Asynchronous Processing: We leverage Python's asyncio to process ML tasks without blocking API requests natively.
Bugs from lack of Validation: Manually checking JSON payload schemas is prone to failure and runtime errors.
Strict Pydantic Models: Runtime error elimination by strongly casting inputs via data schemas immediately.
Strict Pydantic Models: Runtime error elimination by strongly casting inputs via data schemas immediately.
Outdated Documentation: Frontend teams constantly complain about API docs not matching the production code.
Auto-Syncing Swagger UI: Your API documentation updates itself with every commit automatically.
Auto-Syncing Swagger UI: Your API documentation updates itself with every commit automatically.
Scaling Concurrent Users: Standard servers crash during traffic spikes when handling too many open connections.
Blazing Fast Uvicorn: Our infrastructure deployed on ASGI servers effortlessly handles massive parallel traffic.
Blazing Fast Uvicorn: Our infrastructure deployed on ASGI servers effortlessly handles massive parallel traffic.
Fastapi stack we ship on
Tools we use on Fastapi engagements.
Python
PostgreSQL
Redis
AWS
Pytest
Fastapi builds with production discipline
4.9
Clutch rating
We Only Provide Specialists. Not Generalists.
We ship Fastapi products your team can own after launch.
01
API First Architecture
We build decoupled, headless backends that can serve any frontend or mobile client effortlessly.
02
Machine Learning Integration
Deploy Pandas, NumPy and PyTorch models seamlessly wrapped inside robust FastAPI endpoints.
03
Microservices Transition
We help you break down your monolithic app into performant, independent FastAPI Python containers.
Fastapi FAQ
Common questions about Fastapi projects.
*(No answer in HTML)*