🇺🇸 San Francisco

AIOps Platform in San Francisco

An AIOps platform (Artificial Intelligence for IT Operations) ingests telemetry from infrastructure and applications, applies machine learning to detect anomalies and correlate signals, and acts on those insights to keep systems healthy. Modern AIOps platforms execute remediation autonomously instead of merely paging an on-call engineer. SentienGuard detects infrastructure incidents, selects a remediation playbook, executes controlled fixes, verifies recovery and records the evidence.

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Local operating context

Bay Area infrastructure economics are dominated by senior SRE compensation — average loaded cost runs $215K+. Autonomous resolution converts that headcount cost from a linear growth axis to a near-flat one as nodes scale.

A representative 500-node Team deployment is approximately $24,000/year. Pro tier estimate: 500 nodes × $4/endpoint/month annual commit. FX rates as of 2026-05. See /pricing for canonical USD pricing.

Capabilities

Anomaly detection at 3σ

Statistical baselines + ML score deviations; only high-signal anomalies enter the pipeline.

RAG-based playbook selection

1536-dim vector embeddings match incidents to playbooks in ~165 ms with ~95% accuracy.

Confidence-gated execution

High-confidence playbooks run autonomously; lower-confidence ones request Slack approval.

Verification and rollback

Every action re-checks the original signal; failed verifications roll back and escalate.

Immutable audit log

Hash-chained, append-only — SOC 2 / HIPAA / PCI-DSS / GDPR evidence native.

Stack integrations

Slack, PagerDuty, Datadog, Prometheus, Grafana, OpsGenie, AWS, GCP, Azure, Kubernetes day one.