Your AI is already live. Do you know how reliable it is?

A system in production is put to the test every day by real users and real data. Without validation, you do not know how often it gets things wrong, where it fails and what risk that carries.

Data and usage change. A system that was right at launch can drift without anyone noticing. That is why we measure not only current performance, but also how stable and repeatable the behaviour is.

We assess the system along the four quality axes:

• Correctness in the situations where the system is used today.
• Robustness against unexpected and misleading input.
• Data quality: coverage, edge cases, bias and representativeness.
• Behaviour over time: stability, repeatability and deviations.

We do not build models; we validate them. That allows us to assess any AI system independently, regardless of who developed it.

You receive a repeatable test set and the measurements. After an update or a change in your data, you can measure again and compare.