When we reach for it
Data pipelines, model training and evaluation, and internal tooling where the reader is as likely to be an analyst as an engineer. Anywhere the libraries are the reason for the choice, Python is where they live.
Python development
The language the data and machine-learning ecosystem is actually written in, and the fastest way from a question about a dataset to a defensible answer.
What we reach for first
When we would argue against it
A notebook is not a system. We do not ship exploratory Python straight into production; it gets types, tests and a packaging story first, or it gets rewritten in something with a compiler. Performance-critical request paths usually go to Go instead.
What it looks like in delivery
Most of our Python is behind an evaluation harness or a scheduler rather than in front of a user. Typed with annotations and checked in CI, because a pipeline that fails silently on a schema change is worse than one that does not run.
Where this appears on the site
Nothing on this site names it yet
We work in Python, and no case study or service page currently published on this site prints it in its stack. Rather than describe an engagement you cannot check, this space stays empty until one does. Ask us and we will talk you through it directly.
Working in Python?
Tell us what it is running, what it costs you today, and what you need it to do next. A senior engineer will tell you what we would keep and what we would change.