THE FOLLOW-UP WORK PILES UP.
PUT AGENTS ON IT.
Four RAIC agents keep watch between reviews — Shadow AI Triage, Evidence Freshness, Supplier Document Intelligence, and Compliance Drift Watcher. You set how much autonomy each one gets, and every proposal lands in one approval inbox. Your team reviews decisions instead of hunting for work.
Governance dies in the gaps between reviews.
You stood up the program. Intake works, the registry is populated, the controls are mapped. Then the quarter starts and the follow-up work quietly outruns the team: new tools appear faster than anyone triages them, evidence ages, a supplier changes its retention policy, a control drifts from what you approved.
None of that is hard work. It is constant work, and constant work is exactly what a two-person compliance team cannot absorb.
Agents take the watching. Your people keep the deciding.
Four agents that work the queue for you.
Shadow AI Triage
Newly discovered unsanctioned tools get sorted, risk-ranked, and matched to an owner the moment discovery surfaces them, so your team reviews a short list instead of a raw feed.
Evidence Freshness
This agent watches for evidence aging past its useful life and proposes the refresh before an auditor finds the stale artifact first.
Supplier Document Intelligence
Supplier documents and vendor changes get read against the suppliers already in your register, so a shifted retention term or a new subprocessor reaches you as a task, not as news.
Compliance Drift Watcher
When a control stops looking the way you approved it, this agent flags the gap and proposes the correction with the affected clauses attached.
You set the autonomy. You keep the approval.
You set autonomy per agent
Each organization chooses how far an agent can go: off, draft-only, auto-act above a confidence threshold you set, or fully autonomous. Start every agent in draft-only and raise the ceiling as the proposals earn it.
One approval inbox
Every proposal lands in a single queue showing what the agent wants to change, why it proposed the change, and how confident it is. A reviewer approves, edits, or rejects, and that decision becomes part of the governance record.
Scheduled sweeps
Recurring passes across registers, controls, and use cases catch what one-off reviews miss, on a cadence you set rather than one you have to remember.
Notifications when work is waiting
Owners hear about their queue when it fills, so proposals get decided instead of quietly aging in a tab nobody opens.
Metrics that prove the payoff
See what was proposed, what was approved, and how much review time the automation absorbed, so the value shows up in a number your CFO recognizes.
Aslan drafts. Agents act. Humans approve.
Aslan AI generators
You ask, it writes: policies, assessment narratives, board briefs, and incident report books, grounded in your own registry. Aslan waits to be invoked.
Governance agents
Nobody asks, they watch: agents run on a schedule and queue proposals for work you had not gotten to yet. Then a person approves.
Coverage without headcount.
- Cover more AI systems without adding a governance hire
- Catch stale evidence before your auditor does
- Turn vendor changes into tasks instead of surprises
- Keep human approval on every governance decision
- Give owners a queue they can clear, not a backlog they dread
- Show the board coverage rising while headcount holds flat
Governance agents, answered.
Which agents ship today?
Four: Shadow AI Triage, Evidence Freshness, Supplier Document Intelligence, and Compliance Drift Watcher. Each one works a specific part of the governance backlog on a schedule instead of waiting for someone to remember it.
Can an agent change something without a person seeing it?
Only if you decide it can. Each organization sets autonomy per agent: off, draft-only, auto-act above a confidence threshold you choose, or fully autonomous. Draft-only is the default posture for teams that want every proposal reviewed first.
Where do agent proposals land?
In one approval inbox. Every proposal shows what the agent wants to change, why it proposed the change, and how confident it is, so a reviewer decides in seconds rather than reconstructing the reasoning.
How is this different from Aslan AI?
Aslan drafts when a person asks — write this policy, summarize this assessment. Agents watch on a schedule and queue proposals without being asked. Aslan drafts, agents act, humans approve.
How do I know the automation is paying off?
Agent metrics show what was proposed, what was approved, and how much review time the queue absorbed, so you can prove coverage rose without headcount rising with it.
Who should turn agents on first?
Teams governing more AI than they can review by hand, and MSPs running governance across many tenants where per-client follow-up decides the margin.
From the Resources library
Build the business case with the automation buyer's guide.
PUT AGENTS ON THE FOLLOW-UP WORK
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MSP, reseller, and audit-partner programs. Email the partner desk.