Every engineering team knows the pressure of a production incident. Endless logs, fragmented clues, and the race against time to identify what failed before users feel the impact. Root cause analysis remains one of the most difficult and expensive challenges in modern infrastructure operations.
What if AI could drastically reduce that burden?
In this blog series, we explore how we built an AI-powered system capable of analyzing incident reports, filtering massive volumes of logs, navigating complex codebases, and identifying likely root causes in minutes instead of hours. From Kea DHCP to FRR Routing, we tested the system against real-world bugs and benchmarked its performance against actual fixes.
The results were compelling — but so were the lessons from the failures.
Download Part 1 to kick off the series on how we got started with RCA.
