APIs and integrations
We connect CRM, CMS, payment gateways, ERP and internal services through stable APIs.
Why choose FastAPI?
Speed, reliability and modern approach
FastAPI combines speed, auto-generation of documentation and strict validation through type hints and Pydantic
Very fast startup
Start an API or MVP in a matter of hours thanks to minimal setup
Async-first
ASGI-based asynchrony (Starlette) - excellent scalability
Auto documentation
Swagger UI and ReDoc are generated automatically from schematics
Strict Validation
Pydantic + type hints reduce errors and ensure reliability
200–300%Speed up development
40%Fewer errors
+100OpenAPI schemes immediately
99.9%Reliability and scalability
What tasks do we use it for? FastAPI
Below are scenarios where this technology really helps a business: it speeds up launch, simplifies support, or provides the right architecture for growth.
Process automation
We write background tasks, data processors, imports, exports and pipelines.
AI and data-driven products
We are building a service layer for ML models, classification, generation and search.
When technology is suitable and when it is not
Suitable if
- FastAPI is suitable for services that require APIs, integrations, automation and controlled growth of functionality.
- Useful for MVP, internal systems and products with non-standard business logic.
- Suitable when you need quick iteration of hypotheses without unnecessary boilerplate code.
It's better to consider another way if
- Not the best choice if the task comes down to only a standard storefront without backend logic.
- Requires a well-thought-out infrastructure if a very high load and complex distributed architecture are immediately expected.
What is included in the work
- Service architecture, data model and API contracts.
- Authorization, roles, queues, background tasks and integrations.
- Test coverage, logging, monitoring and deployment.
- Transfer of documentation and post-launch support.
Stages of work
- 1Architecture and designWe plan the structure, select async patterns, validation and documentation systems.
- 2Prototype and documentationWe create a basic API with auto-generation of Swagger UI/ReDoc.
- 3Development and integrationWe implement endpoints, connect databases, caches, queues, external services.
- 4Testing and optimizationWe carry out load testing, unit and integration tests, CI/CD.
- 5Deployment and maintenanceSetting up the Uvicorn server, monitoring (Prometheus/OpenTelemetry), secure production.
Frequently Asked Questions
Thanks to its async approach and Starlette, it competes with Go and Node.js in performance
Yes - Swagger UI and ReDoc are automatically generated based on Pydantic blueprints
Yes - type hints + Pydantic allow you to avoid about 40% of errors
Exactly - it is async-ready and easily scales as the load grows.
Yes - Uber, Netflix, Microsoft and others use it in production systems.
Yes - easily integrates with Prometheus, OpenTelemetry, Grafana
If you know Python, mastering FastAPI will take a minimum of time due to its simplicity and docs.