AI Sprints

A precise problem, a testable system, a decision based on evidence.

A short cycle with an agreed scope, criteria written before building and a documented decision.

At a glance

Who it is for: Teams that want to test an answer to a precise problem.
Starting point: A need, data and an expected outcome.
What you receive: A testable building block and a documented evaluation.
What is not delivered: A system in production at scale, a promise of a fixed deadline.
How we decide: With your users, against the scoping criteria.
Possible next step: Move to production, correct or stop, and why.

Need, expected outcome, data and success criteria written before building.

A system that runs on your real cases.

With your users, against the scoping criteria.

Move to production, correct or stop, and why.

A demonstrator, evaluation criteria, a summary of gaps, a decision and next steps.

Duration depends on the problem and is set during scoping. The sprint does not deliver a system in production at scale or promise a fixed deadline.

What should we prepare?

The need, cases to test, accessible data and the people who will evaluate the outcome.

Is production automatic?

It depends on test results and the decision made with you.