3Ο statistical thresholds
Filter noise from genuine deviations before any human or autonomous action.
π©πͺ Berlin
AI anomaly detection uses statistical baselines and machine learning to identify deviations from normal infrastructure behavior. Modern systems score signals above 3Ο 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.
Berlin is Europe's startup capital β SaaS, fintech, mobility. Per-node flat pricing fits early-stage capital efficiency far better than per-metric observability bills.
A representative 500-node Team deployment is approximately β¬22,320/year. Pro tier estimate: 500 nodes Γ $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 β match playbook β execute.
Confidence scoring keeps the autonomous path tight.