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Controls Overview

Controls Overview

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3 mins READ

Introduction

Controls are the rules that decide what your agents may say, accept and do. Everything else in AI Compliance exists to carry them: policies deliver controls to assets, and incidents are what controls produce when something matches.

A control on its own governs nothing. It is a rule waiting for a policy to apply it.

Where to find it

AI Governance > Controls

Access to AI Governance is granted through platform roles. Ask your workspace administrator, or see Settings > Governance > Roles for how permissions are assigned.

What a control is

Three independent choices: a check that decides what counts as a violation, one or more points in the agent's path to apply it on, and an action that says what happens on a hit.

Read the list with that in mind and it stops looking repetitive. The same check watching a different point, or taking a different action, is a different rule with a different effect.

Refer: The three axes and how they interact are covered in Anatomy of a Control. Read it before creating anything.

The Controls table

One row per control, with the count beside the page title.

Column

What it tells you

NAME

What you called it. Opens the control editor.

CHECK

What it detects.

APPLIED ON

Where in the agent's path it runs. Combinable.

ACTION

Flag, Block or Mask.

OWNER

Who is accountable for it.

LAST UPDATED

When it last changed.

The Controls list has no on/off switch. A control is switched on or off inside each policy: open the policy's Controls tab and use the switch on that row. Switching it off there affects that policy only — which makes it the right first move when a control is misfiring in one place and you are not yet sure why.

Controls, policies and incidents

  1. A control defines a rule — Detect this, here, and do that.

  2. A policy applies it to assets — Controls reach agents and models only through policies. A control in no policy evaluates nothing. See Policies.

  3. An incident records a hit — Every match raises an incident carrying the asset, the policy, the control, the action taken and the severity the control graded it with. See Incidents.

The chain runs one way — control, policy, asset, incident — and every debugging question in this section is answered by walking it.

"A control nobody applied is a policy document. A control in a policy is a control."

Controls are reusable by design

One control can sit in many policies. That is deliberate, and it has a consequence worth stating: edit a control and you change its behaviour everywhere it is used.

Before changing a live control, check which policies carry it. A tightening that makes sense for one policy's assets can be badly wrong for another's.

Best Practices

  1. Name for the action, not the check — Block credentials in tool input is readable in a list of eighty. Credentials check is not.

  2. Test before you save — The editor can run sample inputs and show you what the control would do. Use it — it is faster than reading incidents to find out.

  3. Start on Flag — Every control, without exception, until the incident stream looks sane.

  4. Grade severity when you promote — An ungraded control raises incidents nobody can prioritise.

  5. Switch off rather than delete while investigating — Deleting loses the configuration and its policy attachments. Switching a control off in a policy is reversible.

  6. Prefer a prebuilt check where one fits — Cheaper to run than an LLM check, and it is what makes Mask available.

FAQs

Why does the same check appear several times?

Because check, applied-on and action are independent. One detection with three responses is three controls.

Does disabling a control remove it from its policies?

No. It stays attached and stops evaluating.

Can a control apply to models as well as agents?

Controls evaluate traffic; the policy decides which assets are covered, and a policy can cover both.

How do I know whether a control is actually enforcing?