Enterprise AI needs a control plane.
Aureum Health (pronounced "OR-ee-um")
aureumhealth is the AI catalog + governance platform that turns approvals, explainability, drift, cost, and audit readiness into enforceable controls—across EHRs (ie Epic, Cerner, Meditech), vendor AI, internal ML, and agents.
Enterprises are accountable for AI outcomes—even when they don't own the model.
AI governance is broken
Enterprises are deploying AI faster than they can govern it. The consequences are mounting.
No single system of record for AI
AI is spread across Epic, vendor solutions, internal ML models, and agentic tools—tracked in spreadsheets, SharePoint, or tribal knowledge.
No visibility into what AI is running, where, or who owns it.
Governance is paperwork, not enforcement
Policies exist in documents, but nothing prevents unapproved AI from running in production systems.
Compliance gaps discovered during audits, not before.
AI changes in production; no one can prove what changed
Models update, prompts evolve, configurations shift—without version control or change logs.
Impossible to reconstruct AI state during incident investigations.
Explainability is not governed
Some AI outputs need explanations for clinicians or regulators, but access to SHAP/LIME outputs isn't controlled.
Sensitive model internals exposed without authorization.
Drift and performance aren't tied to governance decisions
Model performance degrades over time, but degradation doesn't trigger governance review or rollback.
Underperforming AI continues to affect decisions.
AI cost is becoming a budget line item
LLM tokens, compute, and inference costs are rising with no showback or chargeback capabilities.
Uncontrolled AI spend with no accountability.
What aureumhealth does
A complete control plane for AI governance—from catalog to audit.
AI Catalog
Complete inventory of AI assets with versions, ownership, PHI tiers, and lifecycle state.
Onboarding & Certification
Structured workflows to register, document, and certify AI before production deployment.
Approval Workflows
Security, compliance, and model risk approvals with enforced separation of duties.
Environment Controls
Sandbox and production gating with promotion rules and rollback capabilities.
Install & Rollback
Operational state machine for controlled deployment and instant rollback.
Performance & Drift
Continuous monitoring tied to governance thresholds and automatic alerting.
Governed Explainability
L1/L2/L3 explanations with SHAP/LIME access controlled by policy.
Usage & Cost Governance
Showback and chargeback capabilities with cost allocation by team, project, or model.
Immutable Audit Logs
Append-only audit trail for every action, decision, and state change.
Three steps to governed AI
From registration to operation—every step is governed, auditable, and enforceable.
Register & Classify
Import and categorize AI assets from Epic, vendor solutions, and internal ML—with automatic PHI classification and ownership assignment.
Approve & Certify
Route AI through governance gates for security, compliance, and model risk approval with enforced separation of duties.
Operate Safely
Deploy with environment controls, monitor drift and performance, track costs, and maintain immutable audit evidence.
Why now
The window for reactive governance is closing.
- AI is shipping into systems of record like Epic faster than governance can adapt
- Regulators and auditors want proof of controls, not statements of intent
- AI spend is rising and needs enterprise-grade cost controls
- Enterprises remain accountable for AI outcomes—even when they don't own the model
Built for your stack
aureumhealth sits above execution and data platforms as the AI control plane.
Epic
Execution layer
ServiceNow
Process & ticketing
Snowflake
Data foundation
ML Stacks
Model lifecycle
Complementary to your existing infrastructure—governance layer above Epic, ServiceNow, Snowflake, and ML platforms.