Your security team says no. Your engineering team says they need it. The result? Shadow AI that nobody controls.
Zentinelle policies let you say yes — with guardrails. Define what’s allowed, what’s limited, and what’s blocked. Set org-wide defaults, let teams customize within bounds, and give specific users the access they need.
18+ policy types. Inheritance from org to user. Real-time enforcement. Full audit trail.
Inheritance Model
Policies cascade: Organization → Team → Deployment → Endpoint → User
Set org-wide defaults. Let teams tighten or (with permission) loosen. Grant specific users elevated access. The most specific policy wins.
No manual per-user configuration. No policy sprawl. No gaps.
Real-Time Evaluation
Agents call the /evaluate endpoint before taking action. Zentinelle resolves the effective policy in milliseconds.
Allow, block, or warn — you choose the enforcement model. Blocked actions are logged. Warnings are surfaced. Everything is auditable.
Policy Versioning
Every policy change is versioned. See who changed what, when. Roll back if needed.
Git-like version control for your AI governance. Because “who approved that?” should have an answer.
Zentinelle gives you the granularity to say yes to AI adoption while maintaining the control your security team demands.
