Introducing Complead. One AI-native platform for financial crime compliance. Read the story
New Ready Integrations available Check the new integrations
Agentic AI · Screening

Agentic AML-Risk Ops

An agent reads every screening and monitoring alert, decides whether it is a false positive, a true match or one for a human, and then does what your rule says. You write the rule on a canvas.

Minutes To build a rule
No code Drag and connect
Dry run Before anything changes
Every run Written to the log
Why this matters

The queue is not a workload problem. It is a decision problem.

Most alerts are the same alert. The same name, the same list, the same conclusion, reached again by a different analyst on a different afternoon. What the queue lacks is not people, it is a written-down decision that runs itself.

Repeated

the same clearance, every week

A name clears in March and returns in April because nothing recorded why it cleared.

Uneven

two analysts, two answers

Without a rule the threshold lives in someone’s head, and it moves.

Unwritten

no trail behind the decision

When the regulator asks how the alert was closed, the answer has to be reconstructed.

How it works

Four nodes, then the queue works itself

Scroll to advance
  1. Step 01 The alert arrives

    A screening or monitoring hit enters the queue with its match rate, list origin and entity type attached.

  2. Step 02 The agent forms a view

    It returns one of three decisions with a confidence score: false positive, true positive, or escalate.

  3. Step 03 Your rule branches

    Confidence above 90 closes. Between 70 and 90 goes to an operator with a note. Below that, escalate.

  4. Step 04 The action is written down

    Close, set match status, assign, tag, note, or fire a webhook. Whatever ran is logged with its result.

sanctionscanner / alerts
  • Open alerts1,284
  • Auto-eligible912
  • Median age2 min
sanctionscanner / agent / decision
  • DecisionFalse positive
  • Confidence94
  • BasisDOB + nationality
sanctionscanner / rule / QNB_Rule
  • If confidence> 90
  • ThenClose case
  • ElseAssign operator
sanctionscanner / agent / log
  • ResultApplied
  • RuleQNB_Rule
  • Retained5 years
Alert
Decide
Branch
Apply
The rule builder

One rule, drawn once

This is the whole rule. A trigger, one condition on the confidence score, and three outcomes. Nothing here is code.

What the builder gives you

A rule you can read out loud

01

Visual rule canvas

Drag a trigger, a condition and an action onto the canvas. No scripting, no deploy.

02

43 condition fields

Confidence score, match status, risk level, entity type, amount, channel, article count and more.

03

11 operators

Equals, greater than, between, in, is true and the rest, so a rule reads like a sentence.

04

13 actions

Close, set status, set risk, assign, tag, note, notify, convert to case, webhook, toggle monitoring.

05

Branch and switch

One canvas can hold several outcomes: close the clear ones, route the rest, escalate the few.

06

Dry run first

Run the rule against live traffic without touching a single case, then read what it would have done.

What it leaves behind

Every run is a record

An agent that acts without a trail is a finding waiting to happen. Each execution writes what it saw, what it decided and what it changed.

Applied The rule matched and the action was carried out Logged
Dry run Simulated only, so you can measure before you switch it on Logged
Skipped Matched, but a guard stopped the action Logged
Failed The action could not complete, with the reason attached Logged
FAQ

Before you switch it on

Does the agent act on its own?

Only where you let it. Every action is a node you place yourself, and you can leave a rule in dry run indefinitely.

What if the AI is unsure?

Confidence is a number you can branch on. Most teams auto-close above a high threshold, route the middle band to an operator and escalate the rest.

Can we see what it did?

Every execution writes a log entry: which rule, which node, what it saw, what it changed, and whether it applied, simulated, skipped or failed.

How do we roll it back?

Set the rule to draft and it stops immediately. The log stays, so an auditor can still read what happened while it was on.

Bring a week of your own alerts

We will build one rule on the canvas, run it in dry run against that week, and show you what it would have closed.

Minutes To first rule
No code To change one
Dry run Before it touches a case