Independent, evidence-backed assessment of autonomous AI agents — behavior, safety, and regulatory fit — issued as a verifiable, time-boxed certificate. Sandbox-only testing. Tenant-isolated data. Nothing touches your production systems.
AI agents are increasingly making decisions with real consequences — approving payouts, closing claims, escalating cases, emailing customers — and most of them ship on the strength of the vendor's own claims. Attest exists to replace "trust us" with evidence: an independent, third-party conformance assessment that certifies what a specific agent version actually does, under test, before it's trusted with your production judgment calls.
Every assessment scores an agent against the Attest Framework — a structured methodology spanning capability, robustness and safety, and operational governance. Individual dimension scores roll up into a weighted composite score, but the tiers matter more than the average:
Any Tier-2 (safety or security) dimension failure caps the overall verdict at Conditional — regardless of how high the composite score is. An agent that scores well on task success but can be manipulated through a poisoned document into approving a payout above its authority does not pass because the average looks good. Certification issues on evidence of remediation and a re-test of the specific failing dimensions.
Testing runs exclusively against a scoped, time-boxed sandbox endpoint supplied by the customer, using synthetic data — never production. Ownership of the endpoint is verified before any probe runs. Every irreversible action a probe could trigger — approve, send, close, pay — is routed to a mocked tool layer, never executed against a real system. This is enforced technically, not just requested contractually.
Certification is explicitly scoped to a named agent version, for a named use case, assessed in a specific window — not a general safety claim about the agent in all contexts. The certificate voids automatically on any vendor model or prompt change, and continuous or triggered re-testing keeps certification tied to what's actually running in production, not a point-in-time snapshot from six months ago.
Every assessment maps findings to EU AI Act risk tiering, the NIST AI Risk Management Framework, ISO/IEC 42001, and DPDP or equivalent PII-handling requirements. A certificate is something your compliance team can hand to an auditor or a customer's procurement team — not just an internal engineering artifact.
Composite score out of 100, verdict band, and a dimension tally — how many of the 15 passed, came back conditional, or failed.
Plus an explicit scope disclaimer: named agent version, named use case, assessed window only — and a re-certification date.
Works against any autonomous agent your team builds or buys — single-agent or multi-agent, tool-using or not — via a scoped API connection to your sandbox. Not a source-code audit or pipeline integration.
Independent certification before an autonomous agent touches real customers, claims, or transactions — a governance gate that doesn't rely on the team that built the agent grading its own homework.
Certify a third-party AI agent or copilot before it's embedded in your workflow — evidence-backed assessment in place of a vendor's self-reported benchmark numbers.
Re-certification triggered automatically when the underlying model or prompt changes — so a certificate reflects what's actually running in production, not what was true at launch.
Start with a scoped assessment of one agent — see the dimension-level findings before you commit further.
Book a Certification AssessmentTest Studio proves your code works. Attest independently certifies the AI agents that code powers, before they reach production.
Knowledge Base keeps your regulatory context current. Attest certifies the agents built on top of it against that same regulatory reality.