For years, buying AI detection meant accepting a black box. You gave up any view into how a model reached its verdict, and in exchange you got detection at a scale no human team could match. Most security teams took the deal.
That deal is starting to cost more than it saves.
A Score of 87 Isn't an Explanation
Analysts are buried in alerts they can't interpret, and "risk: 87" tells them nothing they can act on. Compare it to the actual story: this user signed in from a new country, set up a mail-forwarding rule a minute later, then pulled forty times their normal volume out of a finance-tagged SharePoint folder. One version leaves an analyst rebuilding the incident from raw logs. The other lets them triage in seconds. Regulators are closing the gap from the other direction, with the EU AI Act's auditable-logic requirements for high-risk systems phasing in through 2026.
Explanations You Can Defend
When a detection locks an account or blocks a wire transfer, someone has to justify it later — to the employee, to legal, or possibly even in a deposition. "The model said so" does not survive that conversation. Analysts need a call that points to the specific behavioral deviations and connects them to known adversary tradecraft.
That requires a baseline. Abnormal derives a behavioral profile for every identity, so every explanation is concrete: the specific deviation from that baseline, stated in plain language.
A detection that can't show its reasoning has a shelf life. It gets rubber-stamped or tuned out, and either way it quietly stops working. The detection worth trusting is the kind you can explain to someone who wasn't in the room.
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