Discovery scans are open for pilot groups

Turn your AI acceptable use policy into enforced controls.

AI Policy Enforcement

Classify every AI tool once, enforce allow, warn or block on every endpoint and at the firewall, and keep a record of who decided what.

01The challenge

A policy without enforcement is a suggestion.

  • Policy on paper

    Without a technical control layer, compliance relies on self-reporting and violations go undetected.

  • All-or-nothing controls

    If you can’t see which AI tools are in use, you can’t allow the approved ones and block the rest.

  • Drift between policy and reality

    Every delay between a decision and its enforcement is a governance gap.

02The solution

How SuperAlign AI policy enforcement works

Sort every AI tool into allow, warn or block. Newly discovered tools arrive unclassified until someone decides.

03What you get

Key outcomes

  • Technically enforced policy

    Your AI policy is enforced through controls, not a document.

    TrackAI tools with an enforced decision

  • Consistent, real-time coverage

    Decisions take effect at once on the endpoint and network layers.

    TrackTime from decision to enforcement

  • An auditable decision trail

    Approvals, blocks and reviews are logged with owner and timestamp.

    TrackDecisions logged with owner and time

Give us two weeks.
We’ll show you what’s running.

Deploy on your MDM across 25–100 users. Keep the inventory, scored risk view, and a full session record—whether you buy or not.

Day 1Endpoint sensor and browser extension pushed through Jamf or Intune. First results within the hour.
Week 1Full inventory with risk scores, plus one session reconstructed end to end.
Week 2Findings review against criteria you set before we started.
CostNothing. The findings are yours either way.