FastAPI
Our go-to for new APIs: high performance, async support, and automatic, always-accurate documentation. It keeps the backend in the same language as the AI and data work.
Technology
Python development
Python is our default choice for backends, data work and anything that touches AI. It is readable, it has a library for almost everything, and it is easy to hire for, which matters more than raw speed for most business software.
Where it fits
When Python is the right choice
- Your software does data work, machine learning or AI, where Python's ecosystem is unmatched.
- You want a backend that is fast to build, easy to read, and simple to hand to another team later.
- You are connecting several systems and APIs, where Python's libraries save weeks of plumbing.
- You value a large talent pool, so the people who maintain it after us are easy to find.
Where it does not
When we would reach for something else
- For compute-heavy, low-latency work like real-time trading or game engines, a compiled language fits better, and we will say so.
- For a simple marketing site with no real logic, custom Python is overkill and a managed platform is cheaper.
- If your team already runs on another stack they know well, the cost of switching often outweighs the gain.
Our approach
How we build with Python
We build production backends and APIs in Python, usually with FastAPI for its speed and clean, self-documenting endpoints. The same language powers the data pipelines and the AI layer, so there are no awkward bridges between the app and the intelligence behind it. Everything ships with tests, type hints and documentation, and it is yours to run without us.
The ecosystem
The Python frameworks we use
Django
When you want a batteries-included framework with an admin panel, authentication and a database layer out of the box, Django gets a content-heavy or records-heavy product live quickly.
Flask
For small, focused services or when we want full control with minimal scaffolding, Flask stays lightweight and explicit.
Common questions
Python FAQ
For the vast majority of business software, yes. The bottleneck is almost always the database or an external API, not the language. Where raw compute matters, we profile first and optimize the hot path, sometimes in a faster language, rather than rewriting everything.
Usually easily. Because Python is the language of most AI and data libraries, adding an agent, a retrieval feature or a model integration to an existing Python app is one of the cleaner paths there is.
Yes. Python has one of the largest talent pools in software, so you are never dependent on us to keep it running. We write it to be read and hand over full documentation.
Keep exploring
Related technologies
Let’s build it
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