AI in cyber security has a credibility problem — earn it back
Every cyber vendor on the trade-show floor claims AI. Most of it is a thin wrapper over signature-based detection. Artificial intelligence in cyber security done seriously means models that actually reduce mean-time-to-detect, alert volumes that shrink instead of grow, and human analysts who trust the verdicts.
What we build
- Alert triage and prioritisation that materially reduces SOC alert fatigue.
- Behavioural analytics — UEBA-style models trained on your environment.
- Phishing and BEC detection beyond URL blocklisting.
- Log analytics — anomaly detection at petabyte-scale.
- Identity intelligence — privileged-access analytics, lateral-movement detection.
Artificial intelligence security — explainability is non-negotiable
A security analyst who can't see why an alert fired won't trust the system. Every model we ship to a SOC comes with an explanation layer: contributing features, similar historical incidents, and a clear recommended action.