AI practice

AI without the pilot graveyard.

Four capabilities, one method: measure before you build, evaluate before you ship, and be willing to conclude that the answer is not a model.

Advise

An honest assessment of where AI pays for itself in your business — and where it does not.

Build

Retrieval, agents and assistants built as production software — evaluated, observable and safe to change.

Build

Classical ML in production — forecasting, ranking, detection — with the deployment and monitoring that keeps it honest.

Advise

The controls, documentation and testing that let you deploy AI in a regulated environment and defend it.

Find out which use cases survive scrutiny

Six weeks to a ranked, costed portfolio — including the items we recommend skipping.