Healthcare AI Governance Infrastructure

The safeguard standing between hospitals and AI liability

Born from a decade of secure clinical communication informed data infrastructure and AI standards leadership. Evolved into the governance infrastructure hospitals need to deploy AI responsibly.

The Problem

Hospitals are deploying AI they don't control, generating data they don't own, creating liability they can't defend.

Vendor AI runs in third-party clouds. Hospitals don't control the audit trails, can't reconstruct decisions during litigation, and watch governance data leave their jurisdiction entirely. When connectivity fails, oversight fails with it.

D&O carriers are already requiring AI governance questionnaires for coverage binding, with hard mandates expected within 18 months. Rating agencies are adding AI governance to credit methodology. The regulatory environment is removing federal guardrails, but tort liability, insurance scrutiny, and bond rating pressure remain unchanged.

The gap between AI deployment velocity and governance readiness is the largest unpriced risk in healthcare today. And right now, hospitals don't even own the evidence they'd need to defend themselves.

The Principle

If the hospital didn't generate it, store it, and control it, it isn't governance. It's a report from someone else's server.

Medigram's foundational architecture is built on a single premise: governance data belongs to the hospital. Not the EHR vendor. Not the cloud provider. The institution making the clinical decisions owns the evidence trail. On their premises, under their control, on their timeline.

The Solution

Hospital-sovereign infrastructure that executes governance, not just documents it.

Medigram deploys commissioned cyber-physical infrastructure on hospital premises, built on a foundation of secure, offline-capable clinical communication and extended into comprehensive AI governance. The institution owns every audit trail, controls every governance decision, and maintains operations independent of any third-party cloud. Not a dashboard. Not a compliance wrapper. Sovereign infrastructure that owns outcomes.

An autonomous agent orchestration fleet operationalizes governance at scale with capital efficiency that reallocates traditional engineering headcount. Operational coverage mapped to the national standards we helped write, with a structured commissioning process that validates governance in your environment before full deployment.

Sovereignty
Hospital owns all governance data, audit trails, and evidence. On their premises, under their keys
Resilience
Commissioned hardware operates when cloud-dependent systems cannot
Orchestration
Autonomous agent fleet reallocating traditional headcount with capital-efficient automation
Evidence
Cryptographic audit trails built for litigation-grade reconstruction
Independence
Vendor-neutral governance across all clinical AI tools
Compliance
Operational coverage mapped to the national standards we helped author, validated through structured commissioning
5,000+
Hospital and MedTech members in consortium adopting standard in model contract language
CIO Procurement
TTIC cited in CIO leadership AI procurement materials

Built for institutional scale with a permanently lean operating model. The agent fleet is the team. Designed for the power law era.

What to Know & What Your Colleagues Need to See
Data Governance for AI Maturity: TIPPSS Framework Score: - / 100
Trust
Identity
Privacy
Protection
Safety
Security

Bond rating exposure, D&O premium impact, and cost-of-inaction modeling. The financial case for sovereign governance.

Credentials
Standards Authorship
Co-chair, Trust for IEEE UL 2933 data infrastructure standard and healthcare AI governance standards development
Coalition
Chair, multi-institutional trustworthy technology consortium with leading academic medical centers and health systems
Publications
Series Editor, healthcare technology publications with a leading academic publisher
Recognition
National healthcare AI leadership award recipient
Industry
Decade of enterprise healthcare experience across multiple disease areas
Technical
Combined Sciences background with advanced AI/ML and R programming credentials
Why Now

Three market forces converging on a single timeline.

Federal deregulation is removing the compliance frameworks EHR vendors relied on, eliminating their governance differentiation while leaving hospitals exposed to unchanged tort liability and insurance scrutiny. Hospitals now face unregulated AI deployment with no sovereign infrastructure to prove what happened, when, and why.

D&O insurance carriers are moving from questionnaires to mandatory governance endorsements within 18 months. Hospitals without documented AI governance (governance they control, not a vendor report) face premium increases, specific exclusions, or loss of coverage entirely.

Meanwhile, procurement frameworks adopted across thousands of hospitals now reference the governance standards Medigram helped author. The market infrastructure we spent a decade building is becoming the market requirement.

Leadership
Sherri Douville

Sherri Douville

Chief Executive Officer

One of a rare few operating at the intersection of clinical, technical, regulatory, and standards authorship in healthcare AI. A career spent not just advising on governance frameworks, but writing them.

With deep enterprise healthcare experience, advanced technical credentials, and recognized national leadership in AI governance, Sherri built Medigram to close the gap between AI deployment and the infrastructure required to govern it responsibly.

Dr. Arthur Douville

Dr. Arthur Douville

Chief Medical Officer

Former CMO at two health systems with a track record of building and scaling multiple clinical service lines. Grounds the company's technical architecture in real-world clinical operations and physician workflows.

Dr. Art Douville serves as Chief Medical Officer of Medigram and chairs the Clinical Integration committee for the Trustworthy Technology and Innovation in Healthcare Consortium, providing clinical expertise and supervision. His focus is on governance frameworks that guide AI involvement in patient care while protecting the physician's exercise of clinical judgement.

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