Seattle, United States: Glacis Technologies, the Coalition for Health AI (CHAI) and the AIGovOps Foundation announced on Sept. 21, 2026 an agreement to place OVERT (Observable Verification Evidence for Runtime Trust), an open technical specification for verifiable operational evidence from AI systems, under shared stewardship.
CHAI will work with its community to identify healthcare-specific needs and inform continued development. Once the stewardship arrangement formally takes effect, CHAI and AIGovOps will jointly oversee the OVERT specification. Glacis will initially maintain the specification and operate its registry. Stewardship will take effect at the time specified in a separate commencement certificate signed by all three parties.
What OVERT is designed to do#
As AI systems move beyond retrieving, summarizing and analyzing information to supporting decisions and taking actions within healthcare workflows, organizations need more practical ways to understand how those systems operate. Existing governance policies, system logs and vendor documentation provide important pieces of the picture. OVERT is designed to complement them with standardized, independently verifiable evidence about AI actions captured within an implementation’s declared scope.
OVERT defines a common format for evidence generated when an AI system acts. It specifies how to create independently verifiable records showing whether declared governance policies, security controls and oversight requirements were applied at runtime, including the tool calls made by AI agents, without requiring protected content to leave the operator’s environment.
Leadership comments#
Joe Braidwood, founder and CEO of Glacis Technologies, said: “We wrote OVERT because we saw a proof gap in how critical AI safeguards are monitored, especially in healthcare. We built it for everyone to use, our competitors included. That is why CHAI and AIGovOps will steward the standard, with Glacis as a non-voting editor. We will keep building implementations and compete on them like everyone else.”
Ken Johnston, co-founder of the AIGovOps Foundation, said: “Governance that lives in a document cannot be checked. Governance that runs as code can. OVERT gives practitioners a shared way to show that a control executed, and shared stewardship means no single vendor decides what counts as evidence.”
Brenton Hill, Head of Operations and General Counsel at CHAI, said: “Healthcare organizations are asking for more technically rigorous ways to understand how AI operates within live workflows and whether defined safeguards are being applied. By helping steward OVERT, CHAI can bring an open approach to decision-level evidence before our community for scrutiny, input and continued refinement. This is a tangible step toward giving organizations greater transparency into AI-enabled actions and greater confidence in how these systems are governed at scale.”
How OVERT works in practice#
In one example, a healthcare organization requires that a given AI workflow have appropriate authorization, defined data boundaries and clinician review before it acts. With OVERT, runtime evidence documents whether those exact requirements were invoked for that specific AI action, creating a record that can later be reviewed by the organization or another authorized reviewer.
Governance and limitations#
CHAI develops voluntary, consensus-informed resources that help healthcare organizations evaluate and strengthen responsible AI governance across different risk levels and use cases. OVERT provides a technical format that may help organizations translate their own governance requirements into observable evidence within live workflows. Through this collaboration, CHAI will bring the specification before its community to explore its relevance across healthcare environments and help inform its continued development without prescribing a particular AI vendor, model or application architecture.
OVERT is a voluntary technical specification. It does not establish regulatory or legal requirements, certify the safety or effectiveness of an AI system, or determine whether an organization has complied with applicable law. Organizations remain responsible for defining appropriate controls and meeting their legal, regulatory and operational obligations. The collaboration does not establish a post-market monitoring network.
The OVERT specification, governance model and implementation guidance are published at overt.is, where organizations can review the standard and get involved.
About the organizations#
Glacis Technologies develops runtime evidence infrastructure for AI systems. Its technology operates at the point where AI actions occur, enabling organizations to apply defined controls and generate tamper-evident, independently verifiable evidence of how those controls operated. Glacis is backed by:
- AI House
- Geoff Ralston’s Safe AI Fund (SAIF)
- Mighty Capital
- Plug and Play
- Lionheart Ventures
Glacis was recently selected for the Lloyd’s Lab Accelerator, the innovation program of the Lloyd’s insurance market, as one of ten companies in its latest cohort.
OVERT is an open standard released under a royalty-free patent covenant. The published standard and its source text are available at overt.is. Implementation is permitted without royalty; conformance requires independent attestation.
CHAI was started by clinicians. The coalition’s mission is to build the broadest possible consensus across the health ecosystem to help ensure health AI is trusted, secure and safe. The CHAI membership is open and rapidly expanding. Today, it consists of more than 3,000 members including health systems, patient advocacy groups, academia, and a wide range of industry start-ups and incumbents. CHAI is committed to convening and dialogue to achieve consensus.
