Sherlock: AI Incident Response Co-pilot

Production incidents are expensive. The industry average Mean Time To Resolve (MTTR) sits at 4.4 hours — most of it spent manually parsing stack traces, digging through git history, reasoning about code logic, and writing postmortems. Existing tools summarize logs, but none of them can actually reason about your codebase. Sherlock fixes that. Powered by IBM Bob as its core reasoning engine, Sherlock is an AI incident-response co-pilot that takes a raw alert and walks the full on-call cycle automatically: triage the severity, run git forensics to find suspect commits, use Bob to reason over the actual repository and pinpoint the root cause, generate a unified-diff patch ready to open as a PR, and produce a publishable postmortem — all in under 12 seconds. IBM Bob is central to the two hardest steps. The Analyst agent gives Bob full repository context and asks it to reason through the code — not just the logs — to form a root-cause hypothesis with evidence. The Fix agent then uses Bob to generate a precise code patch and regression test grounded in the real codebase structure. This is what separates Sherlock from log-summarization tools. Sherlock ships in three surfaces: a cinematic, slash-command CLI shell for on-call engineers, a Next.js web dashboard with real-time agent visualization, and a FastAPI backend orchestrating a five-stage multi-agent pipeline. A mock mode lets the demo run without a live Bob quota. Key results: MTTR drops from 4.4 hours to ~12 seconds. Root cause identified in under 5 seconds. Fix patch generated in under 4 seconds. The pipeline runs as a background task, so results are always saved to the database even if the client disconnects. Built for the IBM Bob Hackathon 2026.