A managed discipline, not a scattering of scripts — AI accelerates, humans retain authority.
Every rule carries its owner, scope, and version history. Approved rules execute natively inside the client environment — only scores and outcomes return, where failures become tracked issues and posture flows to certification and dashboards.
Pass rates by domain and tier, trend lines, and threshold breaches at a glance.
Every rule's definition, dimension, owner, scope, thresholds, and full version history.
Drafts → review → approval → deployment → tuning → retirement, all attributed.
Rule failures tracked with severity, ownership, aging, and SLA visibility.
Profiling runs inside the client environment against registered assets.
Engine proposes candidate rules from profiles, glossary & reg mappings.
Stewards tune thresholds and approve, reject, or defer — every decision logged.
Approved rules compile to native workloads and run on schedule or event.
Only scores & outcomes return; failures open issues, posture updates.
The dashed boundary is the client cloud — enterprise data never crosses it.
Required data is present.
Values conform to expected formats.
Data agrees across systems.
Data is current when needed.
No unintended duplication.
The Rule Registry is the system of record. AI removes the authoring bottleneck while every rule that runs remains human-approved, traceable, and executed where the data resides.