Taelis tests it, scores it, and catches what's wrong before it ships. So you ship with proof instead of hope.
AI is in production everywhere, and the rules around it just became real. You now have to prove your AI is safe, show what it touches, and answer for what it does. Most teams have no way to.
The EU AI Act is law. It requires you to document how your AI works, govern its risks, and produce that evidence on demand. In force now, with duties landing through 2026.
A tribunal held a company liable for what its chatbot told a customer. The "the AI said it" defence failed. (Moffatt v Air Canada, 2024.)
Most organisations cannot fully see how their own AI handles their data. You cannot govern what you cannot see. (IBM, 2025.)
And the models still hallucinate, leak, and fail quietly in production. Usually a customer notices before you do.
Taelis checks your AI the way a sharp expert would, only harder and faster. We pressure-test it, score how good it is, and block weak work before it ships. Then we keep watching while it runs. The more AI can do, the more it has to earn.
Each does a real job. A few:
Independent models challenge each other until only the strong answers survive.
Real scores for how good the work is, checked against what people prefer.
Every model and data path, drawn from the running system and kept current.
It stops the hollow and the almost-right before they reach anyone.
Every record kept. Every change you can trace.
Real collaboration you can measure, so you see it working.
We're building the layer every AI runs through before anyone trusts it. We break the barrier between what AI can do and what you can safely ship, so people build faster and reach further. Getting AI to work is the start. The bigger question is what we want it to become, and we are building so the answer is a good one.