

An intelligent anomaly detection module that identifies cost spikes, investigates root causes, and pinpoints ownership across cloud, data and AI workloads

Continuously monitors cloud, data, and AI spend to identify high-impact anomalies in near real time.
Radar continuously monitors spend across cloud and data platforms using machine learning. It detects high-impact cost anomalies in near real time without relying on static thresholds, budgets, or predefined alert rules.
When an anomaly is detected, RADAR analyzes services, resources, business units, and usage telemetry. It correlates events, configuration changes, and job activity to explain what changed, when it changed, and why costs increased.
RADAR then models the financial impact and attributes clear ownership. It pinpoints the responsible team, workload, or job, giving you the context needed to take action, escalate with confidence, or automate remediation.
Estimate before you build, with intelligence that understands your architecture.
Static thresholds
ML-driven anomaly dectection
Service-level signals
Service, workload, and business context
What changed
What changed, why and who
Reactive notifications
Just-in-time intervention
Manual response
Policy-governed automated action
Static thresholds
Service-level signals
What changed
Reactive notifications
Manual response
ML-driven anomaly dectection
Service, workload, and business context
What changed, why and who
Just-in-time intervention
Policy-governed automated action
Detect anomalies, understand root causes, and take action before costs escalate.