Rhapsody has launched Guardian, a governance product for controlling how AI agents reach healthcare data and services. The company says Guardian authenticates agents, restricts them to approved operations, applies rate limits and records agent, Model Context Protocol and API activity. A health system could allow an agent to call one service, limit the actions available through it and retain an audit trail of each request. Rhapsody says the product can run independently or alongside its own and third-party integration platforms, and is available now.

The release presents a practical bridge between policy and enforcement. Governance documents can say an agent should use only approved data, but a gateway must translate that rule into credentials, scopes, transaction limits and logs. Healthcare is the announced market, yet the pattern is relevant to banks and insurers using MCP or APIs to expose regulated services. Important details remain for buyers to test: how an agent identity is issued and revoked, whether a delegated user can exceed their own authority, how emergency access is handled, and whether the audit record captures the purpose and outcome of an action rather than merely the call. Product capabilities remain Rhapsody's claims until independently tested.


AI for Leaders: Governance, Risk & Why Strategy Must Come First
Is your organisation adopting AI without a defined strategy or governance? If so, you're not alone — and the consequences range from data breaches to reputational damage to safeguarding failures. AI is a strategic risk, not a silver bullet, and definitely not a magic data fairy. Without clear ownership, rules, and accountability, AI can proliferate across your organisation in ways that cost more — in time, money, and trust — than not using it at all. Speakers: Craig Clark, Director at Clark & Company Information Governance Services, and Stewart Tinson, Project Director, AI-360. You'll learn: Why "understand your why" must precede any AI rollout Which risks senior leaders most commonly overlook — from data leakage to safeguarding How to measure AI value through outcomes, not adoption metrics Why accountability for AI governance sits with the C-suite, not IT or compliance Key topics: AI strategy • Risk appetite • Data protection • Bias & fairness • Safeguarding • AI literacy • Governance models • Return on investment • Executive accountability • AI use case tiering For CISOs, CIOs, and senior leaders who need to govern AI responsibly — before it governs them.
Share this post
The link has been copied!