AI agent verification: evidence, receipts and audit trails

AI agent verification is the process of testing a concrete claim about an agent's action or service outcome against explicit evidence and a known evaluation policy. A useful verification record identifies the claim, the evidence supplied, the rule version, the result, the time of evaluation and an integrity commitment.

This differs from accepting a chat response, screenshot or mutable application log as proof. Those artefacts may help operators investigate an event, but they do not by themselves make the decision portable or independently re-checkable.

A defensible workflow starts with a bounded claim, such as an API responding within a stated threshold or an output matching a committed digest. It then records the acceptance terms before evaluation, preserves the observed measurements, applies deterministic checks and emits a receipt that can be verified again.

Each layer should remain visible. Hiding policy logic behind a confidence score makes it difficult to distinguish a failed measurement, an unevaluated rule and a model judgement.

Logs are essential for debugging, monitoring and incident response. Their weakness is not that they are useless, but that a verifier may need to trust the same system that created and stores them. A receipt narrows the evidence into a stable, canonical record and exposes the evaluation contract.

Strong implementations bind receipts to external measurements, independently controlled signing keys or third-party attestations. First-party receipts remain useful engineering evidence, but should not be described as independent verification without that separation.

A cryptographic digest can detect modification of a receipt, but it cannot make a false input true. Likewise, a deterministic rule can reproduce a decision while still applying the wrong policy. Verification systems need explicit provenance, clock assumptions, missing-evidence handling and versioned canonicalisation.

PactVerity's public Proof Engine accepts explicit latency, uptime, freshness and optional output-integrity criteria, evaluates supplied observations and exports a portable receipt. The same receipt can be imported and checked again against the documented engine behaviour.

The current MVP does not custody funds or settle payments. Its purpose is to make the evidence and decision boundary inspectable before broader protocol functions are claimed.