The standard for public confidence in AI.
People trust businesses and government with life-changing decisions.
AVAAS certifies the AI behind them.
Behind every unvalidated AI decision is a person who trusted the system.
Trust isn’t a feature. It’s an obligation.
Organizations that deploy AI owe something to the people affected by it: proof that the system is fair, explainable, and aligned with human values. Not a promise. Not a policy document. Proof. That’s what we provide.
We don't sell software to the companies we evaluate. No consulting relationship, no platform license, no conflict of interest. The independence regulators and procurement committees require.
Not just a score — the root cause, the exact fix, and the projected improvement. causal attribution decomposes every finding to the specific variables driving it.
Upload your AI's input-output data and receive independent evaluation with causal decomposition and prescriptive remediation. Engagement scoped to your systems, jurisdictions, and risk profile.
You wouldn’t let a student grade their own exam.
The organizations building AI governance tools are doing important work. But when the same company selling you the software also evaluates your compliance, the independence a regulator needs isn’t there. Independence isn’t a feature you can add to a platform. It’s a structural relationship between the evaluator and the evaluated. We built AVAAS around that principle.
A certification report your regulator will actually read.
Not a 200-page compliance document that sits in a drawer. A clear, structured evaluation with a letter grade, causal analysis, and specific fixes designed to be shared with regulators, boards, and customers.
AI governance has many layers. We work at the one where AI reaches a person.
A growing set of tools governs AI, and most of them do necessary work. Each answers a different question, at a different layer of the system. AVAAS starts from a different place than the rest. Not from the model, the paperwork, or the process, but from the person a decision lands on, and whether the system can be trusted at the moment it decides.
We are not the only ones who believe AI needs independent evaluation, and we are glad for that. The difference is our focus. Every layer above governs the system. We stand with the people impacted by the decision.
Let’s talk about what your AI owes the people it affects.
Every conversation starts with understanding your systems, your values, and the people your AI touches. No obligation, no pitch deck — just a conversation about what responsible deployment looks like for your organization.
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