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Industries · Healthcare & Life Sciences

Validate AI where being wrong isn’t an option.

In healthcare, an AI error isn’t an inconvenience — it’s a clinical or patient-safety event. Diagnostic support, triage, documentation, drug-discovery pipelines, patient-facing assistants: each operates where accuracy is non-negotiable and evidence is a legal requirement, not a nicety.

AI use vs. the regulator who governs it
Patient-facing assistantUNVALIDATED · EU AI ACTDiagnostic & imaging modelsNEEDS EVIDENCE · MDRClinical decision supportUNVALIDATED · FDACoding & billing AIPII RISK · HIPAAPost-market monitoringCLEAREDTrial & document AICLEARED

AI touches patients across the care pathway — and each touchpoint has to be defensible to the regulator that gates it. Illustrative; not a measured result.

Where the risk is

The systems you can’t sign off on.

Each of these operates where accuracy is non-negotiable — and none of them is defensible the way it stands today.

  1. A clinical-decision-support model without prospective validation

  2. A patient-facing assistant that can give unsafe or incorrect guidance

  3. An AI/ML medical device that was cleared once and never monitored post-market

  4. A documentation or coding system whose errors propagate into records and billing

The regulatory bar

Clearance is the start of evidence, not the end.

FDA AI/ML medical-device guidance, the EU AI Act and MDR, HIPAA on patient data, and the post-market reality that clearance is the start of evidence, not the end.

Much of what goes wrong with AI medical devices surfaces after deployment — exactly the window one-time testing misses.

What we assure

Validation where safety and evidence are the bar.

We validate AI where safety and evidence are the bar — pre-deployment evaluation, the controls a regulator expects, and the continuous, post-market monitoring that catches degradation before a patient does.

Pre-deployment evaluation

We validate AI where safety and evidence are the bar — before it ever reaches a patient.

The controls a regulator expects

The controls a regulator expects, in place and evidenced — not assumed.

Continuous post-market monitoring

The continuous, post-market monitoring that catches degradation before a patient does.

Make every clinical AI decision defensible to the regulator.

Start with an AI Exposure Snapshot, or talk to us about your specific situation.