Triaging 100’s or 1,000’s of alerts every day keeps security teams very busy. While frustrated by the overwhelming number of alerts, repetitive false positives and endless detection tuning, they are hyper-concerned about missing false negatives. DTonomy’s founders set out to build AI-based cross-correlation and adaptive learning capabilities that instead of looking for anomalies, looks for relationships between alerts; instead of manually figuring out the best detection logic, the system ‘learns-out’ false positives patterns based on security analyst’s activities. The SOC team’s knowledge gained from the time-consuming consolidation and analysis is saved and used to optimize future security operations responses automatically.
Give your rockstar SecOps team a helping hand to:
- Save time on endless detection and automation tuning via AI-based recommendations
- Accelerate analysis with visual grouping of alerts, system behavior and recommended runbook best practices
- Ensure more accurate prioritization of security alerts using AI-based scoring
- Enable faster knowledge transfer within the team via adaptive learning from senior analysts and historical responses
- Reduce the risk of false negatives via continuous context enrichment of security alerts