Python
Our pick for data work, machine learning pipelines, and the AI ecosystem's native tongue.
What we build with it
- AI and LLM backends
- Data pipelines and ETL
- Scraping and automation
- Production APIs with FastAPI
Why we use it
The AI and data ecosystem speaks Python first: model SDKs, vector stores, notebooks, evals. FastAPI makes it a proper production API choice too, typed and quick to build with.
When we don't use it
For plain product backends with no data or AI angle, Node, Go, or .NET usually deploy leaner. Python wins where its ecosystem is the point.
Questions we actually get
Short answers, no sales language. If yours isn't here, ask an engineer directly.
Ask us anythingPython for production APIs, really?
Yes. FastAPI with type hints is a solid production stack, and it keeps AI code and API code in one language. For raw-throughput services we would still compare it against Go.
Do you train custom models or just call APIs?
Both, weighted honestly: most business problems are solved best with hosted models and good engineering around them. Custom training only earns its cost with unusual data and real scale.
Got something to build?
Tell us what you need. An engineer replies, not a sales team.