Security efficiency · AI-driven decisions
Reduce security false positives
Analysts spend significant time reviewing alerts that lack the user, asset, change, threat, and business context required to determine whether they are dangerous.
The record
Telemetry these decisions draw on
- Alert events
- User history
- Device reputation
- Asset criticality
- Threat intelligence
- Change records
- Business role
- Maintenance activity
- Related security events
The questions
What an agent answers
- Is this activity expected or malicious?
- Does it match an approved change or maintenance window?
- What related events increase or reduce risk?
- Should the alert be closed, monitored, or escalated?
- What evidence supports the decision?
"This administrative login is expected. It was performed by the approved deployment account during a scheduled release and matches the last 18 releases."
Related use cases
Browse the full library →Security efficiency
Reconstruct a complete cyber incident
Investigators must manually collect and correlate evidence across many systems to determine how an attacker entered, moved, persisted, and accessed data.
Investigations and forensics · Chief Information Security Officer
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Recommend the safest security response
Containment decisions can protect the enterprise but also create unnecessary business disruption when the scope of compromise is not understood.
AI-driven decisions · Chief Information Security Officer
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Automate repetitive investigation work
Analysts repeatedly gather the same identity, device, threat, asset, and timeline evidence before they can make an initial decision.
Investigations and forensics · Chief Information Security Officer
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