Available in renlyAI runtime
- Approval-gated write actions for connected systems
- Model tier controls and BYOLLM at Enterprise tier
- Audit logs and operational traceability
- Enterprise identity integration through Entra ID SSO
AI Guardrails
AI Guardrails for enterprise AI governance.
AI Guardrails gives enterprise teams clear governance for production AI operations: controlled actions, policy boundaries, access controls, and auditable outcomes.
Governance Model
What AI Guardrails means in practice
Available with Enterprise Governance
- Extended policy enforcement layers
- Advanced evidence and investigation workflows
- Additional incident-response governance controls
- Deeper compliance-oriented operating patterns
Core Capabilities
Guardrail building blocks
Write Approvals
Create and update operations pause until users approve the proposed action.
Audit Logging
Execution and administrative events are recorded for operational review.
Model Governance
Plan tiers and BYOLLM settings govern model access and provider choices.
Identity Controls
Role-scoped access aligned to enterprise identity and organizational boundaries.
Policy Enforcement
Policy checks can be enforced before sensitive operations run.
Evidence Workflows
Operational records support review, investigations, and audit processes.
Governance Architecture
Built on principles, not just policies
Every design decision starts from the same premise: enterprise AI must be safe by default, not safe by configuration.
Model-neutral governance
Your governance policies enforce consistently across every model provider you use. Switch providers tomorrow — your rules don't change.
Dual evaluation layers
Structural rules execute instantly with deterministic outcomes. Semantic rules evaluate context and intent with AI-powered analysis. Both layers run on every governed request.
Enterprise policy templates
Start with ready-made governance templates for common enterprise scenarios — data protection, content safety, compliance, access control. Customize them or build your own.
When in doubt, ask a human
When semantic evaluation confidence is low, the request automatically escalates to a human reviewer. The system chooses safety over speed.
Fail-closed by default
When governance services are unavailable, AI requests are blocked — never bypassed. Your security posture holds even during outages.
Organization-scoped isolation
Policies, evaluation results, and audit data are scoped to your organization. No cross-tenant leakage. Ever.
Correlated evidence chain
Every AI decision is logged with correlation IDs that link request, evaluation, decision, and outcome into one traceable audit trail.
Industry-standard policy engine
Policy evaluation runs on Open Policy Agent (OPA) — the same engine used at Google, Goldman Sachs, and AWS. Not something we built from scratch.
Cloud-boundary evaluation
Semantic evaluation runs within trusted cloud infrastructure. Your data and AI prompts stay inside your security boundary during governance checks.
Control Layers
Runtime controls and enterprise governance extension
renlyAI provides a governance path from day-one runtime controls to stricter enterprise requirements — no rearchitecting needed.
renlyAI: Identity
Entra ID authentication and role-scoped access.
Available now
renlyAI: Write controls
Preview and explicit approval before high-impact writes.
Available now
renlyAI: Audit logs
Execution and admin actions retained for review.
Available now
Extended policy layers
Additional governance policy layers for stricter controls.
Enterprise
Evidence depth
Extended evidence workflows for operational investigations.
Enterprise
Incident safeguards
Additional control points for higher-risk environments.
Enterprise
Compliance support
Expanded governance patterns for regulated enterprise teams.
Enterprise
Evidence and Operations
Signals teams can operate against
| Signal | Why It Matters | Source |
|---|---|---|
| write approval latency | Measures human governance loop for high-impact actions. | renlyAI approval workflow events |
| audit event volume | Tracks security and admin activity by organization. | renlyAI audit logs |
| token usage by tier | Controls spend and plan adherence during rollout. | renlyAI plan limits and usage metrics |
| policy decision latency | Measures governance responsiveness when extended controls are enabled. | Governance policy events |
| investigation turnaround | Tracks how quickly teams can complete governance investigations. | Governance evidence workflows |
See It In Action
A live governance dashboard
Policy enforcement, approval gates, and audit signals operate in a single pane. Here is what teams see when AI Guardrails is running.
Governance Policies
1.2sAvg Approval Latency
3,847Audit Events (7d)
99.6%Policy Compliance
| Policy | Status | Type | Evaluations (7d) |
|---|---|---|---|
| Require approval for work item creation | Active | Structural | 1,204 |
| Block production deploys outside business hours | Active | Structural | 312 |
| Review sensitive data access requests | Active | Semantic | 2,331 |
Concrete Scenarios
How guardrails respond in real operations
Each scenario shows the exact governance path from AI action to auditable outcome.
1
Work item creation approval
- AI agent attempts to create a work item in Jira
- Approval gate policy fires and pauses execution
- User reviews the proposed title, description, and fields
- User approves the action in the governance panel
Outcome: Work item created. Decision and payload logged to audit trail.
2
Model tier enforcement
- AI request targets an expensive model tier
- Model governance policy evaluates plan limits
- Request re-routed to the plan-allowed model tier
- Token usage and routing decision recorded
Outcome: Model usage stays within plan. Routing logged for cost review.
3
Sensitive data escalation
- AI requests access to sensitive project data
- Semantic evaluation assesses context and intent
- Confidence score falls below escalation threshold
- Request escalated to a human reviewer for approval
Outcome: Sensitive access gated by human review. Full evidence chain preserved.
Governance that works on day one — and scales when you need more
renlyAI ships with practical runtime controls from your first login. Enterprise governance layers are available when your compliance requirements grow.
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