Company
AI shouldn't have to choose between capable and accountable.
Why we exist
AI models keep getting more capable and more opaque at the same time. Most teams shipping AI into a real product today have no independent answer to a simple question: how do you know, in real time, that the model making decisions right now is the same trustworthy model you validated before deployment?
We started with a single, narrow belief: a monitor that only reasons about a model's outputs is not enough if the monitor itself can silently break. So we built the self-healing layer first, not as an afterthought bolted onto a dashboard, but as the thing the whole system is organized around.
AuxAI exists to make that answer available to any team running AI that has to work, and fail safely, without someone watching every inference.
How we work
Measure, don't assert
Every claim we make about detection or recovery is backed by a benchmark we can show you.
Black-box by default
We design for teams who can't or won't hand over their model's weights, and build our own trust around that constraint, not against it.
Escalate, don't hide
A system that keeps quietly retrying a fault it can't fix is worse than one that asks for help. We design for the second.
Where we are
Tallinn & Tartu, Estonia
Building close to Estonia's deep-tech and smart-systems research community, with reference deployments already running end-to-end.