AI adoption becomes manageable when governance is part of the operating system.
AI is starting to help with decisions about people's health, in hospitals, and in pro sports, where teams use data about players' bodies to decide who plays and when. Darwin by Medigram is the system that checks the AI: it scores every decision on six kinds of trustworthiness and keeps a permanent record, so whether the stakes are a patient's care or a player's career, nothing happens unchecked and there's always proof. Designed to work on mobile, where the work happens.
Hospital leaders need to move faster without transferring hidden risk to clinicians, patients, security teams, legal teams or the board. The answer is not more AI policy. It is a system that translates institutional policy into enforceable boundaries and produces evidence as work occurs.
A short reader path into Building Darwin, the full CEO Letter.
The executive problem
AI crosses clinical, operational, technical, security and legal boundaries. Each function sees only part of the risk. Institutional performance depends on closing those seams before deployment rather than during an incident.
Where Darwin fits
Darwin screens vendors across the TIPPSS dimensions (trust, identity, privacy, protection, safety and security), then governs consequential decisions through model identification, policy, accountability, security controls, verification and evidence. The record is created at the moment of the decision rather than reconstructed later.
Closing seams before they become escalations
AI decisions in a hospital touch clinical, quality, IT, security, legal, compliance, operations, research, and vendor management, each with its own owner and its own definition of done. When those groups don’t share a single accountable thread, the gaps between them tend to surface as an executive escalation or an incident, not as a policy gap someone caught in advance. This architecture exists to close those seams before that happens.
Why Sherri and the Medigram team
That design came from one person working across those functions directly (standards, architecture, engineering, security, and evidence), so a gap discovered in one area changed decisions in the others immediately, instead of waiting for the next cross-functional meeting. The objective for Medigram now is to build that same continuity into the product and operating model your teams actually use, so it doesn’t rely on recreating that integration internally every time.
Why this can improve both safety and execution
The CEO Letter reports a working remediation loop in which findings become owned engineering actions and are checked again through regression. Governance becomes a mechanism for resolving risk rather than simply documenting it.
What to require from vendors and internal teams
Ask what the system is permitted to do, who remains accountable, where the trust boundary sits, how behavior is tested after deployment, how failures are recorded and remediated, and what evidence will exist if the decision is questioned later.
Need the full architecture and evidence?
The CEO Letter contains the detailed technical rationale, verification loop, standards context and diligence path.