ReverseBits

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

Uber
Spotify
Netflix
Microsoft
Robinhood
Lyft
Cisco
Uber
Spotify
Netflix
Microsoft
Robinhood
Lyft
Cisco

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.

AI Inference Engine project preview

AI Inference Engine

Serving thousands of ML inferences per second using FastAPI backend.

View Project
Trading Data API project preview

Trading Data API

High-frequency asynchronous WebSockets serving real-time crypto prices.

View Project
SaaS Backend Layer project preview

SaaS Backend Layer

A decoupled microservice architecture powering a global CRM platform.

View Project

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 logo

Python

PostgreSQL logo

PostgreSQL

Redis logo

Redis

AWS logo

AWS

Pytest logo

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.

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Let's Figure Out If FastAPI Is Right For Your Project.