Reducing MTTR with AI-Assisted Root Cause Analysis

• MTTR Still Matters — and It’s Still Too High

  According to Uptime Institute, the average Mean Time to Resolution (MTTR) for critical incidents is over 3 hours — even in well-resourced environments. That’s hours of downtime, uncertainty, and customer impact. In most cases, delays aren’t due to lack of alerts, but lack of clarity about what actually went wrong.

• How AI Accelerates Diagnosis

  AI-assisted root cause analysis (RCA) dramatically shortens the time between alert and action. By analyzing telemetry in context — logs, traces, and metrics — AI can surface probable causes, suggest next steps, and reduce the guesswork that typically slows down engineers. It’s not just faster; it’s more focused.

• Real-World Impact, Real Time Saved

  One digital commerce platform implemented AI-assisted RCA across its multi-cloud infrastructure. Prior to adoption, their SRE team averaged 2.5 hours per incident. With AI surfacing correlated anomalies and recommending fixes, their average MTTR dropped to under 45 minutes — a 70% improvement, with fewer escalations and less burnout.

Tired of spending more time diagnosing than resolving?

Observeasy brings AI-driven context to root cause analysis — reducing MTTR and helping teams act with clarity and speed.

📌 Don’t just detect. Understand.

👉 Book a demo and cut hours off your incident timeline.