AI Governance Platform
Govern AI Adoption Without Slowing Innovation
Without centralized governance, organizations face growing exposure across data leakage, identity misuse, and compliance gaps.
Built-In AI Governance From Day Zero
Unified Visibility Across AI, SaaS, and Identity
Proactive Risk Control, Not Reactive Cleanup
Governance That Scales With AI Adoption
Audit-Ready Oversight Without Friction
Govern AI Use Before It Becomes a Risk
Discover Shadow AI Across the Enterprise
- Maintain an inventory of AI apps used with CloudEagle’s proprietary SaaSMap
- Gain visibility into AI usage by comparing browser plugin, Zscaler, and Crowdstrike logs
- See all AI apps in use across the enterprise in one place
Control AI Usage Without Blocking Productivity
- Control AI usage by maintaining a list of approved AI and SaaS tools
- Prevent unsafe AI usage by displaying a flash page when unapproved AI apps are accessed
- Guide users to safe AI usage policies and the approved AI app they should log into
Reduce Identity Risk Introduced by AI
- Ensure AI access aligns with current roles, not historical permissions
- Limit exposure from over-privileged users interacting with AI tools
- Prevent sensitive actions from being performed through unsafe identities
Relevant resources
Frequently Asked Questions
AI governance ensures AI tools are used safely, responsibly, and in line with security, compliance, and risk policies
Employees adopt AI tools faster than IT can review them, creating data, identity, and compliance risks.
AI introduces new risks around data usage, model behavior, and identity misuse that require deeper controls.
AI usage control governs how AI tools are accessed, what data they process, and who can use them.
Over-permissioned users and unmanaged identities can expose sensitive data through AI tools.
Yes. Governance enables controlled adoption instead of blocking AI outright.
It provides visibility, policy enforcement, and audit-ready evidence as regulations evolve.
AI features inside approved tools may process sensitive data without explicit visibility or approval.
It unifies AI discovery, usage control, identity risk, and governance into one operational platform.
As soon as AI tools appear in the environment. So governance is most effective when it starts early.