Payers · providers · trials
Healthcare is already data-intensive; adding generative models without a residency story is how privacy officers lose sleep. AgentAnywhere Sovereign builds agents where OCR, retrievers, and summarizers share the same scope as the rest of your EHR, claims, and trial systems — and produce evidence your IRB and CISO can interrogate together.
PHI
Data class as first control
US / UK / IN
Patterns we map in pilots
BAA
Context for covered workloads
HITL
Clinical gates where required
Regulators expect the same level of control over AI as for core systems — with clearer lineage and data boundaries than most cloud-native stacks default to.
They need to be processed where your BAAs and DPA say they live — not in a public endpoint because it was the fastest to wire.
Narrative generation must be consistent with your policy engine and your appeal process, with line-of-sight to the exact policy version and channel.
Cohort selection and safety surveillance need consent boundaries that survive statistics and privacy review — at the same time you want modern NLP.
A single control plane: jurisdiction-first routing, agent guardrails, and evidence-grade audit you can hand to a supervisor without re-architecting your estate.
Patterns we see in diligence and architecture reviews with regulated customers — not exhaustive, but designed to be concrete for internal steering committees.
Mapped to the frameworks your legal and second-line teams already use — with exportable evidence bundles per region.
Regulatory context: HIPAA, CMS / ONC expectations, NHS DSPT-style patterns in the UK, and emerging national health privacy regimes in India and the Middle East — as a living matrix, not a one-time slide for the board offsite.
We will map your data classes, model catalog, and regulator expectations to a deployable control-plane design — with exportable artifacts for legal and security stakeholders.