AI use-case discovery
that ranks what is worth doing.

We map your processes and the work your teams do every day, then surface where AI genuinely helps: the repetitive, the language-heavy, the judgment-light, and the high-volume. The point is to find real candidates grounded in your operations, not a generic list of trends.

We look as hard for the places AI does not belong. A use case that is risky, low-value, or better solved by a script earns a clear note saying so, because the fastest way to waste an AI budget is to start everywhere at once.

Each candidate is scored on three axes: the value it would create, the risk it carries (including regulatory and data risk), and the effort to ship and run it. The scoring is explicit, so the ranking is a decision you can defend in a board meeting, not a gut call.

The output is a ranked shortlist with a go / no-go per candidate and a recommended first move: the one or two use cases where the value is real, the risk is manageable, and the effort is worth it.

You leave with a prioritized use-case register, the scoring behind it, and a recommended starting point, written to be executed by anyone, including your own engineers. No dependency on SDEN is baked into the next step.

This is the front half of the Audit & Consulting engagement. When you want the full picture, including data- and security-readiness and EU AI Act classification, that is the complete readiness assessment.