Autonomous Governance Agents

The proposal model

An agent never edits your governance data on a hunch. It writes a proposal: what it wants to change, which record it affects, how confident it is, and the reasoning behind it. You approve or reject. Once acted on, the proposal also records who decided and when — so an assessor sees an automated recommendation with a named human accountable for the outcome, which is exactly what every AI governance framework asks for.

The agents

Shadow AI Triage Agent

Runs daily. Clusters unreviewed Shadow AI detections, matches them against the AI catalog, and drafts an AI System or Use Case intake for the tools that warrant one — so discovered tools become governed tools instead of a growing backlog.

Evidence Freshness Agent

Runs weekly. Finds controls whose evidence is stale or missing, drafts requests to the owners, and proposes status changes — before an auditor finds the same gaps for you.

Supplier Document Intelligence

Runs on upload plus a weekly sweep. Reads uploaded data processing agreements, assurance reports, and model cards, populates supplier profile fields from what it finds, and flags contractual gaps.

Compliance Drift Watcher

Runs nightly. Compares your current state against every framework you have enabled and files roadmap tasks for gaps that opened since the last check.

Autonomy levels

Each agent is configured independently, so you can let a low-risk agent act on its own while keeping a high-impact one on a short leash.

Off

The agent does not run.

Draft only

Every proposal waits for a human approval, regardless of confidence.

Auto-apply above confidence threshold

High-confidence proposals apply automatically; everything below the threshold queues for review.

Fully autonomous

Proposals apply automatically. Every write is audited and reversible.

The safety rule that always applies

When an agent has no automatic writer for a given proposal type, that proposal queues for human approval no matter which autonomy level you selected. Automation is never inferred; it exists only where it was explicitly built and reviewed.

The Proposal Inbox

Proposals collect in a reviewable inbox on the Automation Agents screen. Columns are sortable, so you can work by confidence, by agent, by age, or by target record. Approving applies the change and records the approval. Rejecting is terminal: the proposal is closed and recorded, and no governance data is modified. A rejected proposal is a documented decision, not a deleted one.

Runs and metrics

A separate Runs view shows every scheduled and manual execution: when the agent ran, what it examined, how many proposals it produced, and whether the run completed cleanly. Agent metrics summarize acceptance rates over time, which tells you whether an agent has earned more autonomy or needs its threshold tightened.

How this differs from Aslan AI

Aslan AI drafts on request: you ask for a risk assessment, a gap analysis, an executive summary, or a policy, and it produces a draft you edit and accept. Agents work the other way around — nobody asks them anything. They watch continuously and interrupt you only when there is a decision to make. Aslan is the analyst you brief; agents are the monitoring that never sleeps. Most organizations use both.

What gets recorded

Every configuration change, run, proposal, approval, rejection, and automatic write is recorded in your organization's activity log and mirrored to the platform log. There is no unlogged automated action anywhere in the module.

Availability and access

Autonomous Governance Agents are available to Enterprise organizations. Configuring agents, setting autonomy levels, and acting on proposals require Organization Administrator or Workflow Administrator permissions; other roles can view proposals and run history.