AI proposes. Nothing reaches your environment unapproved.
The system arrives with the workflows, records, reporting and controls a regulated lab runs on. When you need something it does not have, AI drafts it — a surface, a query, a workflow over your governed data — and a person reviews and approves it before it goes anywhere.
Watch AI add a feature, governed end to end.
From a plain-language request to a signed-off, access-controlled feature: every step stays compliant and auditable.
An opinionated assistant — entirely under your control.
The assistant is a co-author, not an overlord: ask questions in plain language, get explainable answers, and receive structured proposals you can read, adjust, and approve. Every action stays visible, reversible, and accountable.
- Plain-English questions become safe, explainable queries
- Proposals come with reasoning, impact, and rollback context
- Recommends workflows and surfaces — you decide what goes live
- Every AI action is logged to the same audit trail as people
Bring your own AI. We govern them all the same way.
A governed MCP server exposes your lab's data and operations as standard tools and resources — so any MCP-native client can reason over real context without bespoke connectors.
Agent-ready data
Named warm queries, historical exports, and workspace metadata surface as MCP tools and resources — no custom integration work.
Governed by design
MCP access reuses your existing tenancy, role-based access, and per-tool quotas, with audit-ready catalogs. The same governance applies to every model.
Faster integrations
Connect enterprise AI in hours, not months, using standard contracts — ChatGPT Enterprise, Copilot Studio, or your own agents.
Propose, approve, act — never the other way around.
AI never changes your system unilaterally. It works through a five-step loop that keeps a human in control at the decision point.
- 1
Connect
AI connects through the governed MCP server.
- 2
Observe
It reads your data through typed schemas.
- 3
Propose
It drafts a structured, typed change proposal.
- 4
Decide
You approve, modify, or reject with full context.
- 5
Act
The system applies the change — only after sign-off.
What AI can add to your solution.
Because the platform is defined as code, AI proposals become versioned, auditable configuration — not opaque scripts. Typical proposals include:
Exploring something new? AI-created views open in a clearly-marked testing mode for exploration, kept separate from your validated production workflows until they're reviewed and approved.
Compliant by default. Extensible when you need it.
See how AI adds capability to CMS Life Sciences without ever bypassing governance.