This is about using smart software that learns patterns in your network and systems so it can spot hackers and suspicious behavior much faster than traditional security tools, and often before humans would notice.
Traditional cybersecurity tools struggle to keep up with the volume, speed, and sophistication of modern attacks. Security teams are overwhelmed by alerts, slow incident detection, and manual investigation. AI-enhanced security aims to automate threat detection, reduce false positives, speed up incident response, and better protect complex digital environments.
Potential moat lies in proprietary threat intelligence data, long-term telemetry across many customers, deep integration into existing security stacks (SIEM, EDR, identity, cloud), and Gartner’s research-driven recommendations influencing enterprise buying decisions.
Hybrid
Vector Search
High (Custom Models/Infra)
Continuous ingestion and analysis of high-volume security telemetry (logs, network traffic, endpoints) at low latency while keeping compute costs manageable.
Early Majority
Positioned as thought leadership and guidance on how to apply AI to cybersecurity rather than a single product; focuses on integrating AI into broader security strategy, risk management, and architecture decisions.