An AI health company building AI employees for hospitals needed a production grade Cerner Millennium integration before any hospital would sign. We built the Cerner module of their EHR Proxy SDK, containerized it for repeatable onboarding, and validated it against a live hospital environment, closing the company's first Cerner deal with two AI agents deployable on site.
Talk to Us About EHR IntegrationAI health company building AI employees for hospitals
Cerner Millennium EHR integration for the AI Scribe and AI Receptionist agents
Node.js, pnpm monorepo, Docker, EHR Proxy SDK
Delivered as a fixed scope engagement in 2024, Phase 2 Epic integration followed
The Cerner module made two AI agents production ready inside a live hospital environment.
Hospital deal closed on Cerner Millennium, the company's first
AI agents made production deployable on Cerner: AI Scribe and AI Receptionist
Clinical workflow endpoint categories covered: patient, appointment, encounter, notes, insurance
No hospital signs before EHR integration is proven, and integration logic has to live in the right place, not scattered across every agent.
Hospitals would not commit to a contract until the AI Scribe and AI Receptionist could prove they could read and write inside a live Cerner instance. That meant production grade integration, not a proof of concept.
Cerner Millennium's REST APIs are hospital EHR specific for every workflow. Building that logic inside each agent would mean fixing one Cerner endpoint in two separate codebases every time something changed.
Cerner Millennium's actual API behavior diverges from the published FHIR spec in ways that only surface in live testing, particularly around appointment scheduling validation. We mapped each endpoint against Cerner's sandbox rather than the spec, and built the SDK to handle those behaviors explicitly.
Node.js, pnpm monorepo, Cerner Millennium REST APIs, EHR Proxy SDK, Docker, and an automated end to end integration test suite.
We built the Cerner module of the EHR Proxy SDK in Node.js inside a pnpm monorepo alongside the other agent services. All Cerner Millennium REST API logic lives in the SDK. Neither the AI Scribe nor the AI Receptionist contains EHR specific code. When an agent needs patient data or needs to write a note, it calls the SDK, which handles routing, authentication, error handling, and Cerner's specific API behavior.
We containerized the SDK services for consistent deployment. Each hospital environment has its own tenant IDs, authentication credentials, and Cerner instance specific endpoints. Onboarding a new hospital means configuring environment variables, spinning up the container, and validating against that hospital's Cerner instance.
We built a full automated integration test suite covering the complete Cerner API surface the SDK exposes: patient, appointment, encounter, notes, insurance, and practitioner endpoints. The suite runs against live Cerner sandbox environments, and every endpoint must pass before a hospital goes live.
We configured and validated the full integration for the company's first hospital customer, from SDK configuration through live environment validation. Their AI Receptionist and AI Scribe agents became production deployable on Cerner for the first time.
Talk to us about what a production ready EHR integration layer looks like for your stack.
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