VeriDM's operational loop demonstrates how closed-domain AI agents transform Microsoft Entra ID, Conditional Access, PIM, Intune, Defender, and Graph API signals into Zachman 6x6 mapped, NIST-aligned, CAB-ready identity governance artifacts.
Seven closed-domain agents ingest tenant evidence, classify identity artifacts, validate control intent, and assemble a CAB-ready remediation plan without treating uncited inference as architecture.
The loop constrains AI activity to Microsoft tenant evidence, approved framework mappings, and the VeriIDM methodology so every output remains traceable to a source artifact.
Each finding is mapped across Zachman perspectives and interrogatives to create machine-verifiable architecture records for Microsoft Entra ID, device trust, application access, and data controls.
The scenario controls model Conditional Access hardening, privileged access remediation through PIM, device trust enforcement, and legacy authentication remediation as governed identity changes.
Graph API evidence such as sign-in logs, Conditional Access status, role assignments, device compliance, and Defender signals becomes the source layer for the identity governance corpus.
The reconciliation phase compares documented intent with observed enforcement so identity drift detection becomes a repeatable operating cadence rather than an annual manual review.
Findings are aligned to NIST Zero Trust principles, architecture governance expectations, and the Microsoft Cloud Adoption Framework identity roadmap to support executive and audit review.
The final output is a governance-validated remediation sequence with risk, owner, evidence, and change rationale prepared for change advisory board review.