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A verifiable record of what the AI recommended.

Clinical decision support, triage, and diagnostic AI now shape care. When an outcome is reviewed, for patient safety, liability, or audit, clinicians and hospitals need to show exactly what the system recommended, on what data, and when. AskLedger makes that record tamper-evident.

The stakes

In healthcare, "what did the AI say?" is a safety question.

When an AI recommendation contributes to a clinical outcome, a faithful record of that recommendation matters for the patient, the clinician, the hospital's risk team, and any subsequent review. Ordinary logs can be edited and rarely capture the exact model version, precisely what a safety investigation needs.

The same receipt AskLedger signs to prove your AI savings seals each recommendation as a signed receipt that records hashes of the inputs and output, provable evidence without duplicating protected health information.

Use cases

See it end to end.

Clinical AIA decision-support recommendation is reviewed after an adverse event
Workflow
1
AI offers a recommendationsurfaced to the clinician at point of care
2
Receipt seals the recommendationinput hash, output & model version recorded
3
Outcome is reviewedsafety / M&M / liability review opens
4
Exact recommendation shownverified, with the model version of the day
  • The moment it matters

    A review board asks precisely what the AI recommended and whether the clinician acted on it.

  • Without proof

    The model has since been updated; the original recommendation can't be reproduced.

  • What the receipt proves

    The exact recommendation, inputs (by hash), and model version at the time, a clear factual basis for review.

Regulatory pressure

Aligned to patient-safety and privacy regimes.

See full regulatory coverage →

Make clinical AI reviewable, without copying PHI.

Talk to us about evidencing decision support, triage, and diagnostic AI.