Theo’s tooling drowns him in false positives because it scores everyone against one threshold. He needs anomalies measured against each person’s own normal.
Static thresholds flag busy analysts constantly and miss the quiet outlier.
Without per-person normal, ‘80 downloads’ means nothing.
Risk signals live apart from the document audit trail, so context is lost.
The same audit trail that proves your governance also powers insider-risk detection. Each person is scored against their own learned baseline — a 3 a.m. mass export lands as HIGH, while a genuine power user stays within baseline instead of being constantly false-flagged.
Baselines are built per actor from the same audit trail that proves governance.
Volume spikes, off-hours activity, sensitivity escalation, and breadth combine into a score.
A 3 a.m. mass export lands HIGH; a genuine power user stays within baseline.
Each alert links to the exact documents and actions on the ledger.
No — baselines are learned per actor, so legitimate heavy users stay within their own normal.
From the same hash-chained audit trail that records every ingest, read, export, and disposition.
Combinations like a volume spike plus off-hours plus sensitivity escalation across many distinct documents.
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