AI that works within healthcare, not around it.
AgentOS is a governed AI workforce with six capability tiers, twelve named workers, review gates where they matter, and measurable outcomes. Every action traces back to evidence. Every boundary is explicit.
Six tiers. Clear rules at every level.
Not all AI is equal. AgentOS classifies every capability into one of six tiers, and each tier comes with explicit, enforced rules about autonomy and review.
Twelve agents. Named jobs. Explicit boundaries.
AgentOS ships with twelve pre-defined agents. Each has a scoped job, a Care Graph grounding and a hard boundary it cannot cross — regardless of prompt.
Reads inbound referrals across forms, email, fax and APIs. Extracts facts, flags missing items and suggests triage.
Handles booking, reminders, check-ins and low-risk administrative tasks across patient channels.
Drafts clinical notes, visit summaries, discharge packs and letters grounded in the Care Graph.
Watches pathways for overdue tasks, breach risks and blocked work. Nudges owners and escalates.
Monitors refill gaps, missed doses and outreach effectiveness across medication cohorts.
Assembles supporting documents, maps payer checklists and drafts rationale for prior authorisation.
Reviews completeness, protocol deviations and audit gaps across episodes and documentation.
Suggests codes, checks completeness and surfaces leakage flags across billable activity.
Clusters, prioritises and routes tasks, messages and alerts across operator inboxes.
Generates weekly performance narratives, anomaly explanations and cohort comparisons.
Drafts risk assessments, intake assessments and review summaries from structured observations and history.
Compiles shift handovers, transfer-of-care notes and between-team summaries across open episodes and alerts.
Six things other AI platforms don’t do.
AgentOS is not a chat widget bolted onto an EHR. It is a first-class AI runtime inside careos — graph-grounded, evidence-first, governed end-to-end.
Care Graph-grounded reasoning
AI operates over a structured graph of patients, tasks, medications and messages — not free-text RAG over PDFs. Every answer traces to graph nodes.
Agent Studio
Admins configure agent goals, approval rules, prompts and escalation paths without writing code. Policy is owned by the operations team, not engineering.
Simulation & replay
Test policy changes against historical events before release. See exactly how a new routing rule or approval threshold would have behaved last quarter.
Evidence by default
Every AI action stores provenance — model, prompt, inputs, sources, reviewer and outcome. Audit is free, not an afterthought.
Outcome-linked learning
Agents are measured on closed-loop outcomes: contact success, overdue reduction, time saved, override rates. Not vanity metrics.
Multi-channel patient AI
One governed layer across portal, SMS, email, voice and app. Consistent policy, consistent provenance, consistent safety posture.
Nine non-negotiable governance requirements.
Provenance, minimisation, registries, evaluations, review, classification, tenant overrides and customer-facing analytics. Each is specified and enforced.
Model, provider, version, prompt, inputs, timestamp, actor and decision path stored for every AI action.
Redaction, routing and retention controls applied before any model invocation, per tenant and market.
Model registry, prompt registry, feature flags, market restrictions and tenant controls managed centrally.
Quality, hallucination rate, safety, override rate, drift and latency tracked against golden sets.
Review queues, rollback paths, feedback capture, incident handling and bad-output suppression.
AI use cases classified by regulatory and safety risk before enablement. Tier gates enforced.
Tenants can tighten autonomy, review thresholds and permitted providers below the platform default.
Time saved, approval rates, override rates and outcome deltas exposed to customers, not hidden.
Per-tenant, per-agent, per-use-case metering of AI spend, throughput and incident rates — tied to commercial metering and review.
Four rules AgentOS will never break.
These are enforced at the platform level, below tenant policy. No prompt, no configuration, no override can cross them.
- 01No AI autonomously prescribes, discontinues, or alters medication.
- 02No AI silently writes to the legal clinical record.
- 03Clinically influential outputs require human review before action.
- 04All submissions to external parties remain human-accountable.
See AgentOS working on real care workflows.
We’ll walk through the tiers, workers, governance controls and evidence exports on your own service lines — not a generic demo dataset.