Disclosure presentation
Was the recorded notice shown before the linked AI action?
One evidence layer for the health system, AI vendor, broker, carrier, and reviewer. It records what the system did without exposing a chart.
Each receipt makes one narrow claim. A verifier checks the signature, ordering, links, and fixed fields. A reviewer can accept or reject the claim without seeing the underlying patient record.
Was the recorded notice shown before the linked AI action?
Did one party sign the proposed artifact, purpose, and retention terms?
Did two different keys agree on the same terms and the order of transfer?
Was the policy version, scope, and digest fixed before it took effect?
Was a deletion event recorded against the earlier policy and erasure receipt?
Does the observed serving configuration match the one that was evaluated?
The same receipt package can move with the system through ordinary governance and the moments when evidence suddenly matters.
Fix the policy, disclosure, custody terms, and evaluated model configuration.
Give the broker or carrier aggregate evidence that the controls kept running.
Reconstruct what was presented, transferred, retained, purged, or changed.
Let the other side verify each signed claim independently.
Choose a public example. This page sends the signed object to the production Hive verifier and prints the result returned by the live service.
These are signed public examples. They contain no patient information. A valid result proves only the narrow claim named by the receipt.
Epic's Seismometer asks whether a model performs and is fair across local populations. Hive records whether the deployed system followed the disclosure, custody, retention, purge, and evaluated model-change rules around that model.
Use Seismometer or another validation system to measure accuracy, fairness, drift, interventions, and outcomes.
Use Hive to give an outside reviewer a signed record of what the deployment did and when it did it.
Hive is not affiliated with or endorsed by Epic. The comparison describes complementary functions.
We will map one live healthcare AI workflow, issue the relevant receipts, run an evidence drill, and shape the export around the questions your legal, compliance, risk, or underwriting team already asks.