How do we know the model works before it goes to production?
With a held-out question test: your experts write questions the model never saw, the threshold is set in advance and results are reported by segment. Your team grades it, not ours. A version is released only if it matches or beats the previous one, after a week with internal administrators and the written sign-off of the process owner.
It is metric 1 of the governance framework and rule 4 of the non-negotiables. The evaluation report goes into the evidence file. Reference method: NIST AI RMF, action MS-2.3.
Sources
- DEBIR governance framework, metric 1 and rule 4.
- NIST AI Risk Management Framework 1.0 (2023).
Regulatory framework verified against primary sources on November 1, 2026.
- What data leaves my perimeter when I use private AI?
- Do you use our customers’ data to train the model?
- How are data subject rights and the right to object to automated decisions handled?
- What happens if there is a data breach in the system?
- How is the system isolated from the internet and the public cloud?
Discovery sessions, no commitment
With technology, compliance and two process owners. Includes an offline demonstration prepared for your sector, without using your company’s data.
Inventory and obligations
Data in four levels and a first review of what your sector requires.
Three candidate use cases
And the Assessment proposal. The Discovery is credited against the Assessment.
Founding clients program
Three seats, with an explicit discount in exchange for a publishable case and a reference.
Terms
Discovery and evidence pilot at no cost, Assessment at a discount, in exchange for a publishable case, a reference and feedback. Continuous operation is always paid at list price.