See the attempt
An AI access attempt is seen in the browser.
A single company-wide GenAI switch rarely matches how organizations work. Engineering, finance, and legal carry different risk profiles — and different approved tools. AI Data Shield policy management turns those differences into enforceable rules at the browser: start from templates, then refine by team, role, or use case.
Those rules feed the Decide step after Detect and Verify. SSO answers “is this session trusted?” Policy answers “is this tool allowed for this group?”
Policies are what Decide evaluates after Detect and Verify know who is trying to open which tool.
An AI access attempt is seen in the browser.
SSO status is checked so identity is known before a decision.
Your policies apply — by team or role as configured — allow, block, or flag according to the rules you set.
Hub step 03 — Set Policies — is where templates and team rules are established. Step 04 — Monitor & Refine — is where you tune them as approved platforms and org structure change.
Different departments can have different GenAI rules without maintaining four disconnected processes.
Templates give a shared foundation; customization stays available where risk demands it.
The same Detect → Verify → Decide path for everyone; only the policy inputs differ by group.
Policies live with the browser extension deployment, alongside your existing security stack.
People in groups with approved, SSO-verified tools keep a productive path. Groups with tighter limits see those limits enforced at open — consistently with what security published — rather than informal tribal knowledge about “which AI we’re allowed to use.”
How It Works overview → Enterprise Features · Policy Management →
SSO-Gated Access · Real-Time Blocking · Policy Management · Audit Trail & Reporting
Request a demo, or continue through the How It Works feature path.
Request a DemoReal-Time Blocking · Audit Trail & Reporting · Request a Demo