Integrity
Does policy, workflow and authority behave as intended under normal operation?
A claim-based assurance service for testing whether governance properties remain observable, repeatable and reviewable when AI systems actually execute.
Runtime assurance begins with a bounded claim. The objective is not to certify intelligence in the abstract, but to test specific governance properties under stated conditions.
Does policy, workflow and authority behave as intended under normal operation?
Do equivalent conditions produce stable, explainable behaviour and evidence?
What happens under incomplete, contradictory, adversarial or out-of-policy inputs?
Can material outputs and decisions be traced through the runtime path?
Do governance properties remain consistent when models or infrastructure change?
Can a reviewer determine exactly what passed, failed or remains unresolved?
Test design can combine baseline, repeated, variant and adversarial cases depending on the claim being assessed.
Depending on scope, an assurance engagement can produce a test contract, execution record, comparison results, exceptions, reviewer disposition and a bounded statement of what the evidence supports.
Passing a defined test contract does not prove that an AI system is safe under every possible condition. Assurance remains scoped to the claim, environment and evidence actually tested.
We can structure the validation question, acceptance criteria and evidence boundary before any execution work begins.