One AI Agent For Every Control

Each Agent monitors one control against the criteria, thresholds, and guardrails you set, reviews the evidence as it arrives, and brings your team in only when something needs their judgment.

Controls AI Agents

Evidence in. Gaps closed. No chasing.

Complyance continuously monitors your controls. Evidence is auto-generated through your integrations, held against the criteria your team wrote, and any gap is flagged back to the evidence owner before anyone needs to look. Set it up once, and your team moves from reviewing everything to handling the exceptions.

1

Map your controls

Select your frameworks and controls, or bring your own control set. Every control gets its own AI Agent, monitoring against the checks your auditors and your teams define.

2

Connect the systems your evidence lives in

Connect the systems you want, scoped to the specific data you choose to share. Nothing beyond that, and no client data is used to train LLMs. Evidence is then auto-generated on the cadence each control requires.

3

Define what each AI Agent checks for

Start from our auditor-drafted review criteria, edit them, or write your own. You define what counts as sufficient evidence and what gets flagged, and every decision comes back with the reasoning attached, so it holds up in an audit conversation.

4

From gap to closure, not just detection

A gap is flagged to the evidence owner, then turned into remediation actions that each carry an owner and a due date, followed up until they’re resolved. Significant findings can be escalated as risks at the click of a button, so what surfaces in January isn’t still open in April.

Frequently asked questions