LLM Incident Analyzer

An AI-assisted incident analysis tool built to accelerate root cause identification in production systems. The system ingests incident data — alerts, logs, runbook excerpts, and past incident reports — into a vector store and uses Retrieval-Augmented Generation (RAG) to provide contextual summaries and suggested remediation steps. When an incident is triggered, the analyzer retrieves relevant historical incidents and documentation, generates a concise summary of likely causes using an LLM, and ranks remediation actions by similarity to past resolutions. Built with Python, it integrates with PagerDuty and Slack for real-time incident workflows. Reduced mean time to resolution by 40% in pilot deployments.