Every alert worked. No analyst burned out.
An AI analyst that triages, investigates, and remediates every data incident end to end — escalating to your team only when human judgment is genuinely needed.
The whole analyst loop, not just triage.
Six stages every incident passes through — Argus runs all of them, and shows its work at each.
Triage
Every alert ranked by blast radius — data sensitivity, access breadth, destination risk.
Investigation
Identity, device, lineage, and history pulled automatically — the incident reconstructed as a story.
Verdict
Benign, coached, or true incident — each with confidence and the evidence that produced it.
Remediation
Close the share, revoke the token, quarantine the file — guardrailed playbooks, approval where required.
Escalation
The 2% that need a human arrive as a finished case file — not a raw alert at 2 AM.
Learning
Every analyst correction tunes the verdict model — the queue gets quieter every month.
An analyst, not an alert filter.
Three things Argus does that a SOAR playbook can't.
It asks the questions an analyst would.
Who is this user? Is the device healthy? Where did the file come from? Has this happened before? Argus runs the whole line of questioning — with lineage and Discovery data already in hand — before any verdict.
Fixes it — within lines you draw.
Containment runs automatically; destructive actions wait for a human yes. You decide which is which, per playbook — and everything it does is reversible and logged.
Humans get cases, not noise.
The rare escalation arrives as a finished brief — timeline, evidence, verdict rationale, and the one decision that needs a person. Your analysts start at the interesting part.
It works the alerts the platform creates.
Discovery finds it, Classification labels it, DLP stops it — and the SOC analyst closes the loop with evidence.