Out.Cloud's AIOps platform uses machine learning to cut alert noise by 40%, correlate events across your entire service mesh, and trigger automated runbooks — before your on-call engineer even wakes up.
From raw telemetry to automated remediation — AIOps closes the loop your current tooling leaves open.
ML models score every incoming alert by business impact and blast radius. Low-priority noise gets suppressed automatically. High-impact events get enriched with context and routed to the right team — before anyone is paged unnecessarily.
Explore capabilityDynamic baselines learned from your actual traffic patterns. Anomalies flagged before they cross SLO thresholds — giving teams seconds to respond, not minutes.
Explore capabilityTopology-aware ML clusters related events across services into single incidents. One ticket per root cause — not one ticket per symptom.
Explore capabilityYour tribal knowledge, encoded as executable playbooks. When an incident matches a known pattern, the runbook fires automatically — scaling, restarting, rerouting traffic, or rolling back a deployment — all without human intervention. Mean time to resolution drops from minutes to seconds.
Explore capabilityA single pane of glass across all services, all clouds. Real-time MTTA, MTTR and alert noise metrics — with drill-down into any incident timeline.
Explore capabilityFour stages. Every stage closes the loop your current tooling leaves open.
We connect to your existing Prometheus, Grafana, Datadog or OpenTelemetry stack. Golden signals and SLO boundaries are defined per service — no rip-and-replace required.
ML models learn your service topology and historical alert patterns. Dynamic baselines are established. The system begins mapping symptom clusters to probable root causes.
Alert routing rules, escalation paths and suppression policies are tuned to your team's actual workflows. Noise reduction typically exceeds 40% within the first month.
Runbooks encoded as version-controlled YAML. Known incident patterns remediate themselves. Your on-call engineers are paged for decisions, not repetition.
AIOps isn't a dashboard product. It's an operational practice. We build it so your SRE teams actually trust it.
Every alert, every correlation, every automated remediation is logged with full context. Evidence packs for ISO 27001, SOC 2 and NIS2 generated on demand. No scrambling at audit time.
We embed our SRE practices alongside your teams — defining SLOs, error budgets, and escalation policies that map to your business context, not a generic template. Regulated industries need 99.9%+ uptime. We build for it.
Prometheus, Grafana, Datadog, PagerDuty, Elastic, OpenTelemetry — we add intelligence on top of what you have. No forklift migration. No six-month onboarding. Observable results within weeks.
Prometheus · Grafana · Datadog · PagerDuty · Elastic · OpenTelemetry · Kubernetes · Jaeger · Loki · Alertmanager · New Relic · Fluentd
Trusted by leading enterprises
30 minutes. We'll map your current alert landscape and show you exactly where ML can close the gap.
No commitment. No vendor pitch. Just the conversation your ops team needs.