Why
AI is now production infrastructure. Every enterprise will need an AI catalog and governance control plane. aureumhealth is building it.
"Enterprises are accountable for AI outcomes—even when they don't own the model. No AI CMDB or control tower exists for runtime behavior, explainability, and cost." - Aureumhealth - fills that gap.
AI governance is the next enterprise control plane
Just as enterprises built control planes for cloud (Control Tower), identity (IAM), and process (ServiceNow), they will need a control plane for AI.
Visibility
Know what AI is running, where, and who owns it
Control
Enforce governance policies, not just document them
Evidence
Prove compliance to auditors and regulators
Six governance gaps that create enterprise risk
These aren't hypothetical risks. They're the challenges we hear from CIOs, CISOs, CNIOs, and compliance leaders every day.
No single system of record for AI
AI is spread across Epic, vendor solutions, internal ML models, and agentic tools. It's tracked in spreadsheets, SharePoint, or tribal knowledge.
No visibility into what AI is running, where, or who owns it. Auditors ask questions that take weeks to answer—if they can be answered at all.
aureumhealth provides a centralized AI catalog with complete inventory, ownership, versioning, and lifecycle state for every AI asset.
Governance is paperwork, not enforcement
Policies exist in documents, review boards meet quarterly, but nothing prevents unapproved AI from running in production systems.
Compliance gaps discovered during audits, not before. Policy violations occur without detection until something goes wrong.
aureumhealth enforces governance with approval gates, environment controls, and certification workflows that block unapproved AI from production.
AI changes in production; no one can prove what changed
Models update, prompts evolve, configurations shift—without version control, change logs, or state tracking.
Impossible to reconstruct AI state during incident investigations. 'What was the AI doing when this happened?' becomes unanswerable.
aureumhealth maintains immutable audit logs and version tracking for every AI asset, enabling point-in-time reconstruction.
Explainability is not governed
Some AI outputs need explanations for clinicians or regulators, but access to SHAP/LIME outputs isn't controlled or audited.
Sensitive model internals exposed without authorization. No evidence of who received what explanations.
aureumhealth provides tiered explainability (L1/L2/L3) with role-based access controls and complete audit logging.
Drift and performance aren't tied to governance decisions
Model performance degrades over time, but degradation doesn't trigger governance review, escalation, or rollback.
Underperforming AI continues to affect decisions. Performance problems become governance problems only after incidents.
aureumhealth ties performance thresholds to governance workflows, triggering automatic review, alerts, and rollback when limits are breached.
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. Departments can't budget for AI, finance can't forecast it.
aureumhealth provides usage tracking, cost allocation, showback dashboards, and budget alerts for AI spend governance.
Why existing tools don't solve this
Enterprises have invested in control planes for cloud, identity, process, and data. AI governance is the missing layer.
| Existing Tool | What It Covers | AI Governance Gap |
|---|---|---|
| AWS Control Tower | Cloud infrastructure governance | No AI asset tracking, model risk, or explainability |
| IAM / Privileged Access | User and service identity | No AI lifecycle governance or audit evidence |
| ServiceNow | Process and ticketing workflows | No AI catalog, performance monitoring, or cost governance |
| Data Catalogs (Collibra, Alation) | Data asset inventory | No AI runtime behavior, drift detection, or explainability |
| MLOps Platforms (MLflow, Kubeflow) | Model training and deployment | No enterprise governance, audit evidence, or cost controls |
aureumhealth is the AI governance layer that sits above these platforms, providing the visibility, control, and audit evidence that none of them deliver.
Quantify the value for your organization
Use our interactive calculator to estimate the financial impact of aureumhealth based on your current AI environment and governance challenges.
ROI Calculator
Calculate your potential savings with aureumhealth
Your AI Environment
Risk & Incidents
Audit & Staff Costs
Annual Savings Breakdown
Detailed Savings
Key Insights
- Save approximately 744 hours annually on governance tasks
- Potential to prevent 2.1 incidents per year
- Reduce audit preparation time by 120 hours annually
* These calculations are estimates based on industry benchmarks and typical customer outcomes. Actual results will vary based on your specific environment, implementation, and usage patterns. Contact us for a detailed assessment tailored to your organization.
Why this matters for your enterprise
Risk Reduction
Enforceable controls mean governance violations are prevented, not discovered after incidents.
Faster Deployment
Standardized governance workflows accelerate AI deployment by removing ad-hoc review processes.
Cost Control
AI spend governance ensures costs are visible, allocated, and controlled at the enterprise level.