

Scoutflo is an AI-powered Site Reliability Engineering platform designed to automate incident response and debugging processes for cloud-native applications. The platform serves as a personalized AI SRE that helps engineering teams quickly identify and resolve production issues.
Key capabilities include automated root cause analysis with confidence scoring, AI-powered anomaly detection to identify problems before they impact users, and intelligent correlation that connects signals across monitoring, logs, and infrastructure. The platform features automated playbook execution, guardrails and approvals for safe automation, and auto-generated postmortems that save documentation time. It provides real-time insights into reliability, costs, and risk across infrastructure.
The platform operates through a four-step process: connecting infrastructure tools, detecting and diagnosing issues through AI-powered analysis, remediating problems with automated fixes, and learning from incidents through continuous improvement. Scoutflo's Kepler engine functions like a senior SRE available 24/7, understanding service dependencies and delivering evidence-backed root causes with concrete fix steps.
Benefits include dramatically reducing mean time to resolution (MTTR), eliminating alert fatigue by triaging what matters, and enabling teams to focus on critical issues. The platform helps engineers become 10x faster by automating safe fixes and providing instant, explainable root cause analysis. It simplifies cloud-native deployments with AI-driven automation, allowing teams to ship faster and scale smarter.
The product targets fast-moving engineering teams, SRE teams, and developers working with cloud-native infrastructure. It integrates with Kubernetes, AWS, Terraform/Git, CI/CD systems, Grafana, Datadog, Prometheus, Sentry, Slack, and various other monitoring, cloud, and collaboration tools.
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Scoutflo targets fast-moving engineering teams, SRE teams, and developers working with cloud-native infrastructure. The platform is designed for technical teams that need to create, simulate, and manage AI-driven workflows visually. It serves organizations using Kubernetes, AWS, and various monitoring tools who want to automate incident response and reduce manual debugging efforts.