Governance Built Into the Runtime
Atlas™ operationalizes the Accentus AI Operating Model™ (AAOM) — a comprehensive governance architecture designed for regulated and mission-critical AI environments.
Governance is not layered on afterward. It is embedded into the operational fabric of the platform.
9 Domains. 47 Controls.
Each control is mapped to lifecycle phases, risk tiers, and implementation priority. Expand any domain to explore its controls.
AAOM™ Runtime Enforcement
Most governance frameworks are static documentation. Atlas™ operationalizes AAOM™ — every domain maps to live runtime enforcement.
| AAOM™ Domain | Atlas™ Runtime Enforcement |
|---|---|
| Risk Tiering | Dynamic policy activation based on use-case classification |
| HITL Controls | Approval workflows with structured escalation routing |
| Audit Logging | Immutable operational ledger for every transaction |
| Vendor Risk | Third-party model governance and supply chain controls |
| Guardrails | Runtime I/O mediation via NeMo Guardrails |
| Lifecycle Governance | Deployment gating with rollback controls |
| Data Governance | Policy-scoped retrieval boundaries and access controls |
| Compliance | Continuous conformity monitoring and regulatory tracking |
7-Phase AI Lifecycle
End-to-end governance gates ensuring compliance at every stage — from ideation through decommissioning.
Ideation
Problem definition, use case scoping, and initial risk tiering.
Data
Data sourcing, governance, quality assurance, and bias assessment.
Development
Model design, training, experimentation, and documentation.
Validation
Testing, benchmarking, fairness, explainability, and red-teaming.
Deployment
Approval gates, system integration, HITL, and operational readiness.
Monitor
Performance tracking, drift detection, incident management, and retraining.
End
Decommissioning, retirement, and knowledge transfer.
4-Tier Risk Classification
Every AI use case is classified by risk tier — determining which controls apply, the depth of monitoring, and whether deployment is permitted.
Unacceptable
Prohibited use cases. No deployment permitted.
High Risk
Maximum controls. All 47 applicable. Continuous monitoring.
Limited Risk
Enhanced controls. Transparency & documentation required.
Minimal Risk
Baseline controls. Core governance and monitoring.
Regulatory Compliance Mapping
AAOM™ controls are mapped to 8 major global regulatory frameworks — providing audit-ready compliance posture from day one.
NIST AI RMF
AI Risk Management Framework
EU AI Act
European AI Regulation
ISO/IEC 42001
AI Management System
EO 14110
US Executive Order on AI
OMB M-24-10
Federal AI Governance
NIST 800-53
Security & Privacy Controls
NIST CSF 2.0
Cybersecurity Framework
IEEE 7000
Ethical System Design
6-Level Maturity Scale
Assess and advance your organization's AI governance maturity — from ad hoc processes to industry-leading continuous improvement.
Non-Existent
No awareness of AI governance requirements.
Initial
Ad hoc processes. Reactive and unstructured.
Developing
Documented processes. Beginning to formalize.
Defined
Standardized across the organization.
Managed
Quantitative measurement and optimization.
Optimizing
Continuous improvement. Industry-leading.
7 Defined Governance Roles
Clear accountability and oversight structure for AI programs at every level of the organization.
AI Governance Board
Strategic oversight and policy direction
Chief AI Officer (CAIO)
Accountability owner for AI programs
Internal Audit
Independent assurance and compliance verification
AI Ethics Officer
Ethical review and bias mitigation
AI Risk Manager
Risk identification, assessment, and monitoring
AI Security Officer
Security architecture and threat response
Compliance Officer
Regulatory alignment and audit readiness
Autonomous Agent Controls
AAOM™ includes specialized governance for agentic AI systems — covering agent autonomy levels, tool-use permissions, execution boundaries, multi-agent orchestration oversight, human-in-the-loop checkpoints, guardrail enforcement, and full decision-chain audit traceability.
Agent Autonomy Levels
Defined tiers with escalation and override
Tool Use Governance
Permission boundaries and action logging
Orchestration Oversight
Multi-agent coordination and chain-of-custody
Human-in-the-Loop
Mandatory checkpoints with real-time intervention
Guardrail Enforcement
I/O validation and behavioral boundaries
Audit & Traceability
Full decision chain logging for every action
The Governance Operating Architecture Powering Atlas™
AAOM™ is not a consulting framework. It is the governance operating system embedded into every Atlas™ deployment — ensuring that AI operates within defined boundaries, under structured oversight, with immutable accountability.
From ideation through decommissioning. From minimal risk to high risk. From individual models to autonomous agents.