Trustable AI.

Logs are not proof

Every AI system today keeps logs. Logs are text in a database, and text in a database can be edited, trimmed, or quietly lost. When an agent approves a refund, rejects a candidate, or moves money, "we have logs" is not an answer a regulator, a customer, or a court will accept. The bar is tamper-evidence: a record that cannot be rewritten after the fact without the rewrite being obvious.

The decision is a chain, not a moment

An agent's action is the last link in a chain: the data it saw, the context it was given, the model it called, the tools it touched, the intermediate steps it took. If any link is missing, the action is unexplainable. We think the unit of audit is the whole chain, captured as it happens, hashed and sealed so that every step can be replayed and checked later.

You cannot prove what a model thought

Closed models do not expose their weights, and no amount of cryptography changes that. The honest claim, and the useful one, is different: you can prove what went in, what came out, what was done with it, and that your analysis of the decision is faithful to the record. That is enough to answer the questions that matter. Who decided, based on what, and can we check it.

Regulation is arriving faster than tooling

Rules that demand exactly this kind of record are already scheduled across the EU, the US, and beyond, with penalties large enough to change board agendas. Most companies will meet that wave with screenshots and good intentions. The ones that run agents at scale will need trust infrastructure that was designed for it. We are building that layer first, because nothing else we build matters without it.