3ฯ statistical thresholds
Filter noise from genuine deviations before any human or autonomous action.
๐ฎ๐ช Dublin
AI anomaly detection uses statistical baselines and machine learning to identify deviations from normal infrastructure behavior. Modern systems score signals above 3ฯ as anomalous and trigger a remediation pipeline, not just an alert. SentienGuard detects infrastructure incidents, selects a remediation playbook, executes controlled fixes, verifies recovery and records the evidence.
Dublin is the EMEA HQ city for most US hyperscalers. SRE teams here own region-wide infrastructure spanning EU-GDPR and NIS2 boundaries โ autonomous remediation's audit trail covers both with one log stream.
A representative 500-node Team deployment is approximately โฌ22,320/year. Pro tier estimate: 500 nodes ร $4/endpoint/month annual commit. FX rates as of 2026-05. See /pricing for canonical USD pricing.
Filter noise from genuine deviations before any human or autonomous action.
Metrics + logs + events fused into one incident hypothesis.
Anomaly embedded into vector โ match playbook โ execute.
Confidence scoring keeps the autonomous path tight.