When we use Python.

Where the work is on data: collecting it, transforming it, analysing it. For automating processes someone used to do by hand, for internal tools, and for everything involving artificial intelligence models, where the available libraries have no equivalent elsewhere.

Also for backends, when the library that already exists matters more than execution speed.

This is where it pays off: a lot to process, little pressure on response times.

The technologies we work with

When we do not use it

When response times must be tight and predictable, or memory use needs controlling: we use Rust there. When demand consists of many open connections waiting, Node.js costs less.

What we have used it for

[REDACTED]
ScaleApplied AI company
From prototype to production product.
2 yearsActive
[REDACTED]
BuildPublishing & Media
Reading app — delivered on the launch date.
1 yearCompleted

The way we work is the same across technologies: peer review before release, separate environments, and automated pipeline checks. How we work

If you have a project to build, grow or recover: Build · Scale · Rescue

When we use Python.

The technologies we work with

When we do not use it

What we have used it for

From prototype to production product.

Reading app — delivered on the launch date.

Python