the same clearance, every week
A name clears in March and returns in April because nothing recorded why it cleared.
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.
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.
A name clears in March and returns in April because nothing recorded why it cleared.
Without a rule the threshold lives in someone’s head, and it moves.
When the regulator asks how the alert was closed, the answer has to be reconstructed.
A screening or monitoring hit enters the queue with its match rate, list origin and entity type attached.
It returns one of three decisions with a confidence score: false positive, true positive, or escalate.
Confidence above 90 closes. Between 70 and 90 goes to an operator with a note. Below that, escalate.
Close, set match status, assign, tag, note, or fire a webhook. Whatever ran is logged with its result.
This is the whole rule. A trigger, one condition on the confidence score, and three outcomes. Nothing here is code.
Drag a trigger, a condition and an action onto the canvas. No scripting, no deploy.
Confidence score, match status, risk level, entity type, amount, channel, article count and more.
Equals, greater than, between, in, is true and the rest, so a rule reads like a sentence.
Close, set status, set risk, assign, tag, note, notify, convert to case, webhook, toggle monitoring.
One canvas can hold several outcomes: close the clear ones, route the rest, escalate the few.
Run the rule against live traffic without touching a single case, then read what it would have done.
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.
Only where you let it. Every action is a node you place yourself, and you can leave a rule in dry run indefinitely.
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.
Every execution writes a log entry: which rule, which node, what it saw, what it changed, and whether it applied, simulated, skipped or failed.
Set the rule to draft and it stops immediately. The log stays, so an auditor can still read what happened while it was on.
We will build one rule on the canvas, run it in dry run against that week, and show you what it would have closed.