Enterprise AI portfolio intake & risk registry
Discover, tier, and register every AI tool in the organization — including the ones nobody declared.
Govern the clinical AI portfolio you already have.
For CMIOs, Chief AI Officers, and AI steering committees accountable for every algorithm touching patient care.
What makes this hard
The portfolio is larger than the inventory
Clinical AI tools proliferate faster than governance: embedded vendor algorithms, departmental purchases, and shadow usage nobody registered.
Oversight is a committee, not a runtime
Steering committees approve policies, but nothing enforces them at the moment a tool executes on a patient's data.
Regulatory exposure is compounding
ONC HTI-1 transparency requirements and Joint Commission responsible-use expectations demand documentation most portfolios cannot produce.
Where we engage
Clinical deployment gating
Runtime enforcement of oversight protocols: validated inputs, physician sign-off gates, escalation paths, and change control.
ONC HTI-1 compliance documentation
Source-attribute transparency and outcome monitoring evidence, generated from the systems' actual operation.
Clinical outcome & safety review
Pre-registered outcome questions, silent-run baselines, acceptance and override rates by unit, explicit sensitivity/specificity trade-offs signed into each Context of Use, and a standing harm-review cadence — not incident-triggered.
Our practice designed and operated enterprise AI governance across a 180-tool portfolio at a multi-state integrated health system.
Engagement references are named under NDA. Request a private reference conversation.
The pillars doing the heavy lifting here
Portfolio Command Center
Leadership sees the whole AI portfolio through evidence, not dashboards of vanity metrics.
Runtime Boundary Enforcement
Out-of-boundary use is rejected at runtime — the Context of Use is enforced, not just documented.
AI Portfolio Intelligence
The portfolio's cost, risk, and value are measured — and every change keeps a human in the loop.
Framework anchors
ONC HTI-1Joint Commission Responsible UseISO/IEC 42001NIST AI RMF 1.0
Every engagement is structured in the evidentiary language these frameworks expect — so the work survives reviewer scrutiny, not just internal approval.
Start with an honest census.
Start with an honest census: what is actually running, what decisions each system touches, and who owns each one — including the tools nobody registered.
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Prefer to see the work first? Walk through an eight-week pilot, step by step