Agents act. AVAAS verifies how they behave before you hand them the keys.
An agent does not draft a decision for a human to approve. It executes. It sends the email, moves the money, changes the record, calls the next tool. Every property you assumed about a chatbot changes when the output is an action, and the verification bar rises with it.
The decision point becomes an action point
With a predictive model, a human usually sits between the score and the consequence. With an agent, the consequence is the output. The blast radius scales with every tool, credential, and system the agent can touch, and mistakes compound across steps faster than monitoring catches them.
The question is no longer whether the model's answer is right. It is what the agent will actually do across the situations you never wrote a test for.
What keeps agent deployments exposed
No human between decision and effect
When the agent acts directly on systems and people, an error is not a bad suggestion. It is a completed transaction, message, or record change.
It may behave differently under test
UK AI Security Institute testing in April 2026 found frontier models can recognize evaluation settings, and the institute reported it could not claim high confidence that behavior under test predicts behavior in deployment.
Agents call agents
Once agents delegate to other agents and tools, behavior emerges from the chain, not any single model, and no vendor attestation covers the chain.
How AVAAS evaluates an agent
Does it hold to its boundaries?
Scenario-based testing probes what the agent does with real tool access under pressure, ambiguity, and adversarial prompts, not what it says it would do.
Will it behave the same in production?
Eval-awareness is assessed directly, and sealed deployment verification confirms the system in production is the system that was certified.
Can you show your work afterward?
The result is documented, third-party evidence of conformity to a published standard at the decision point, ready for your board, your customers, and your regulator.
Agents are being deployed faster than any prior class of AI system, and the organizations deploying them carry the consequences of every action taken. Certification puts an independent check between the agent and the keys.
Related AVAAS coverage: Customer-facing AI · Fraud & account access · Certification.
Check your exposure before you certify
Agentic AI Risk Checklist
Check where an AI agent takes actions on its own and where that creates exposure.
Open tool →AI Assurance Gap Analyzer
See the gap between your current AI governance and what a defensible standard requires.
Open tool →AI Vendor Liability Screener
Find out who is liable when a third-party AI vendor drives a decision that harms someone.
Open tool →Find out what your agents would actually do.
Tell us what your agents can touch and what they are allowed to decide, and we will scope a behavioral evaluation before the next one ships.
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