Framework-aligned tracking
Map model and portfolio activity to relevant obligations and controls across major AI governance frameworks and internal review programs.
Feature · Compliance workflows
Operationalize AI compliance work beyond static checklists
SentinelAI helps organizations structure recurring governance work around obligations, evidence, remediation, and review status across the EU AI Act, NIST AI RMF, ISO 42001, and internal policies.
What this area covers
Compliance workflows are built for teams that need governance activity to be repeatable and reviewable. Instead of tracking obligations in documents alone, SentinelAI organizes evidence, framework mapping, and unresolved gaps in a workspace tied to the underlying AI systems.
Related product areas
- Model registry
Maintain a governed inventory for AI models and use-case context with lifecycle state, ownership, risk posture, and supporting evidence.
- AI systems
Track governed runtime systems that combine models, approved use cases, datasets, release state, and readiness into one operational record.
- Dataset governance
Bring datasets, lineage, approvals, taxonomy-backed controls, catalog integrations, and quality gates into the AI governance workflow.
- Evaluation suites
Define governed prompt evaluation suites with baselines, regression thresholds, run evidence, and release-blocking posture.
- Release governance
Manage AI-system release records with approval state, rollback references, dependency snapshots, and invalidation handling.
- Governance cases
Coordinate alerts, findings, remediation, evidence posture, SLA deadlines, and closure outcomes in one shared case workspace.
- AI governance intelligence
Detect risks, duplicate AI initiatives, overlap, and rationalization opportunities across governed records with explainable, human-reviewed analysis.
- Reports and certificates
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.
- Vendor AI governance
Register third-party AI vendors, structure due diligence, and connect external AI dependencies to internal governance records.
Core capabilities
Built to support production governance work
Evidence capture
Centralize supporting artifacts, review notes, and status updates so teams can prepare for internal review, audit, or external stakeholder questions with less scrambling.
Remediation workflow
Turn unresolved gaps into follow-up actions instead of leaving them as passive findings in a spreadsheet or slide deck.
Conformity assessment support
Maintain assessment-oriented workflows and evidence trails for teams that need deeper review around regulated or high-risk AI use cases.
Target users
- Compliance officers coordinating evidence and policy alignment
- Risk leaders tracking unresolved governance gaps and remediation
- Legal and assurance stakeholders preparing for review cycles
- Cross-functional AI governance committees managing approval readiness
Governance value
- Helps teams move from one-off compliance projects to repeatable operating workflows
- Improves visibility into open gaps, evidence status, and ownership
- Creates a more durable audit trail around decisions and control activity
- Supports portfolio-wide reporting without claiming automatic compliance outcomes
How teams use it
A practical operating flow for this feature family
Step 1
Map obligations
Associate models and programs with the frameworks, requirements, and internal controls that matter to them.
Step 2
Collect evidence and resolve gaps
Attach supporting materials, review status, and remediation actions in the same workflow where teams assess readiness.
Step 3
Report progress with context
Summarize where obligations are progressing, where exceptions remain, and what needs executive or governance review next.
Continue exploring
Explore how SentinelAI connects adjacent governance workflows
Model registry
Maintain a governed inventory for AI models and use-case context with lifecycle state, ownership, risk posture, and supporting evidence.
AI systems
Track governed runtime systems that combine models, approved use cases, datasets, release state, and readiness into one operational record.
Dataset governance
Bring datasets, lineage, approvals, taxonomy-backed controls, catalog integrations, and quality gates into the AI governance workflow.
Evaluation suites
Define governed prompt evaluation suites with baselines, regression thresholds, run evidence, and release-blocking posture.
Release governance
Manage AI-system release records with approval state, rollback references, dependency snapshots, and invalidation handling.
Governance cases
Coordinate alerts, findings, remediation, evidence posture, SLA deadlines, and closure outcomes in one shared case workspace.
AI governance intelligence
Detect risks, duplicate AI initiatives, overlap, and rationalization opportunities across governed records with explainable, human-reviewed analysis.
Reports and certificates
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.
Vendor AI governance
Register third-party AI vendors, structure due diligence, and connect external AI dependencies to internal governance records.