ZippyOPS AI is an AIOps platform built by the engineers who manage production infrastructure at scale. Anomaly detection, alert correlation, automated remediation and predictive operations — applied to your Kubernetes clusters, cloud accounts and CI/CD pipelines.
Most AIOps products are built by software companies who hired some ML engineers. ZippyOPS AI was built by the engineers who manage Kubernetes clusters, cloud infrastructure and CI/CD pipelines for enterprise clients every day — and got tired of reactive, noisy operations.
Every feature in ZippyOPS AI came from a real problem on a real client engagement. Anomaly detection tuned for infrastructure metrics — not financial data. Alert correlation that understands Kubernetes pod topology. Remediation playbooks written by senior SREs.
The result is an AIOps platform that actually works in production — not a demo that looks impressive but breaks on real data.
Four AI-powered capabilities that transform how your team operates production infrastructure.
ML models trained on your infrastructure metrics detect anomalies that static thresholds miss — catching saturation, degradation and unusual patterns hours before they cause incidents. Tuned per-service, not one-size-fits-all.
Intelligent grouping of related alerts into single incidents using topology-aware correlation. A 1,000-alert storm becomes 20 actionable notifications — with root cause highlighted, not buried.
Pre-built remediation playbooks for common failure patterns — pod restarts, node pressure, certificate expiry, disk saturation and more. Automated resolution with full audit trail and human-in-the-loop escalation for anything uncertain.
Forecast resource exhaustion, failure likelihood and capacity limits before they impact users. Alert on predicted problems with 20-minute lead time — warning your team, not your customers.
Single pane of glass for infrastructure health, active incidents, predicted issues and remediation history. Built on Grafana with ZippyOPS-designed dashboards for Kubernetes, cloud and application tiers.
Native integrations with Prometheus, Grafana, PagerDuty, Slack, Kubernetes, AWS CloudWatch, Azure Monitor and GCP Cloud Monitoring. Plugs into your existing observability stack without replacing it.
The shift from reactive to intelligent operations is measurable from day one.
Clients consistently see 90%+ reductions in alert volume within the first week. Not by silencing alerts — by correlating related signals into single actionable notifications.
When ZippyOPS AI identifies the root cause and suggests the remediation, on-call engineers spend minutes confirming and approving — not hours investigating.
Predicted failure patterns caught 20 minutes before user impact. Engineering teams shift from firefighting to proactive capacity management and planned responses.
Clients report £1M+ annual savings from reduced incident frequency, faster resolution and elimination of the engineering time wasted on false alarm investigations.
Engineering teams report dramatically reduced on-call stress when alerts are meaningful, root cause is pre-identified and automated remediation handles the routine failures overnight.
Visit ai.zippyops.com to explore the platform, or book a demo with a ZippyOPS engineer to see it applied to your infrastructure.