This is like giving your IT operations team a smart autopilot: it continuously watches all your systems, spots issues before they become outages, and automatically takes many of the routine actions a human operator would—only faster and at much larger scale.
Reduces outages and performance incidents in complex IT environments by automatically detecting anomalies, correlating alerts, and triggering remediation actions—cutting manual monitoring, triage time, and human error.
Deep integration into existing IT toolchain (monitoring, logging, ticketing), access to historical operational data for model tuning, and process lock-in around incident workflows and automations.
Hybrid
Vector Search
High (Custom Models/Infra)
High-volume telemetry ingestion (logs, metrics, traces) and real-time inference latency for anomaly detection and automated remediation decisions.
Early Majority
Positioned specifically as AI-first operations automation (AIOps) focused on resilience and agility—less about simple alerting dashboards and more about closed-loop automation from detection to remediation across modern, cloud-native stacks.