Key takeaways
- H2O Driverless AI trains classification models on your labeled security events to tell threatening activity from routine noise.
- Anomaly detection and clustering find activity that matches no known signature, even in unlabeled, noisy data.
- Every score comes with reason codes, so your security team, auditors and the board can see why an event was flagged.
- Models run beside the security tools you already have, using their logs and alerts as inputs.
More signals than your analysts can read
Your security team watches thousands of devices, users and applications across data silos that were never designed to talk to each other. Every tool raises its own alerts, and most of them turn out to be routine.
Attackers do not wait for signatures. Phishing, malware and malicious downloads change shape faster than rules are rewritten, so the events that matter hide among the ones that do not. When something does get through, you have to explain what was detected, when, and why your team acted the way it did.