Learn how InferTrust™ provides cryptographic proof of AI device behavior during FDA enforcement actions including 483 observations, warning letters, and recalls
When FDA takes enforcement action against an AI/ML-based medical device, the manufacturer must demonstrate what the algorithm did, when it did it, and under what validated conditions. InferTrust™ FDA Enforcement (Patent Pending) provides this capability by creating cryptographically signed decision records for every AI inference, model update, and performance metric throughout the device lifecycle.
During an FDA enforcement action, investigators typically request evidence of algorithm behavior for specific time periods, patient populations, or clinical scenarios. InferTrust™ decision records answer these requests with verifiable proof. Each record is sealed at the point of inference with the model version hash, confidence score, input feature fingerprint, active policy version, and decision action. Because records are signed with device-bound cryptographic keys before any network transmission, they cannot be fabricated, backdated, or altered after the fact.
Form 483 observations require a written response within 15 business days. InferTrust™ decision records enable manufacturers to quickly identify the root cause of any algorithmic issue, precisely scope which patients or clinical scenarios were affected, document the corrective action with cryptographic proof of the fix, and demonstrate ongoing compliance with post-correction decision records. For warning letters and consent decrees, InferTrust™ provides the continuous monitoring evidence that FDA requires to verify sustained compliance.
When FDA orders a recall of an AI medical device, the manufacturer must determine the scope of the problem: which devices, which software versions, which time periods, and which patients. InferTrust™ decision records provide the definitive record of exactly which model version was running on each device at every point in time, enabling precise recall scoping that minimizes patient disruption while satisfying FDA requirements.