Questions

We test AI systems and the data behind them, whether you bought them or built them, and tell you how often they are right, where they go wrong and what to do about it. When the evidence supports it, we also help you fix or upgrade them.

Vendors measure their own systems on tests they choose, and internal teams are often grading work they built or bought. An outside test on your own data gives you a number nobody involved had a reason to inflate.

The error rate on your real cases, the causes behind the errors, a recommendation tied to your decision and the test set, which you can rerun after every update.

Yes, after the evaluation and only where the evidence supports it. When an acquirer, investor or auditor hires us to test another company's AI, we stop after the evaluation, and when we compare vendors for you, our own products are not among the options.

Yes. We can work with you directly or through your diligence or audit firm.

It doesn't have to. When you need it, we can run every analysis on your own compute, inside your systems. We follow GDPR and your rules for data retention and deletion. See security and data for the details.

It depends on the decision and on how quickly we can reach the data. In the first call we tell you whether a useful test can finish before your deadline.

We quote after the first call, once we know the decision, the systems involved and the data.

In machine learning, a seed sweep reruns an experiment with different random starting points to check whether a result is replicable or was luck. We run the same check on the AI systems companies depend on.