Verifiable AI Evidence: What It Means and Why It Matters
Verifiable AI evidence is the ability to prove, with cryptographic certainty, what an AI system decided, when, and under which policy. Learn how organizations create tamper-evident audit trails.
Why Traditional AI Logs Are Not Evidence
Traditional AI logs have critical gaps that prevent them from serving as verifiable evidence. They have no cryptographic binding between the log entry and the actual inference. They offer no tamper detection, so records can be edited or fabricated without detection. They lack policy linkage, so auditors cannot verify which rules governed the decision. And they have no offline integrity, meaning decisions made at the edge may never reach a central system.
How InferTrust Creates Verifiable Evidence
- Inference: The AI model produces a decision that needs to be preserved.
- Sign: InferTrust cryptographically signs the decision record using device-bound keys at the point of inference. The signature covers model version, input feature hash, confidence score, policy version, and decision action.
- Store: The signed record is written to an append-only ledger. Integrity does not depend on the storage layer or network path.
- Verify: Any party with the appropriate key can verify that a decision record is authentic and unaltered, even years after the original decision.
Industries That Need Verifiable AI Evidence
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