3Ο statistical thresholds
Filter noise from genuine deviations before any human or autonomous action.
πΊπΈ Dallas
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.
Dallas-Fort Worth carries one of the largest data-center concentrations in North America. Multi-tenant operators run SentienGuard agents at fleet scale to keep MTTR contractually defensible.
A representative 500-node Team deployment is approximately $24,000/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.