AI-Powered Root Cause Analysis with Sentry + n8n

Wanted to work with me? https://cal.com/abhi.vaar/n8n My Linktree: https://linktr.ee/iamvaar What if a Sentry alert could do more than tell you that something broke? In this project, I built an AI-powered incident investigation workflow using n8n, Sentry, GitHub, PostgreSQL, and Slack. Instead of simply forwarding error notifications, the workflow gathers context, checks previous incidents, analyses recent code changes, and generates a structured investigation report. How the workflow works Sentry: Triggers the workflow when a new issue appears. PostgreSQL: Checks for duplicate investigations and retrieves historical incident data. GitHub: Fetches recent commits for additional context. AI Agent: Analyses the issue, evidence, severity, potential root causes, and affected users. PostgreSQL: Stores the investigation results. Slack: Sends a structured incident summary with a direct link to Sentry. The goal is to help developers move beyond basic error notifications and get a useful starting point for investigating production incidents. Important: The AI produces hypotheses, not guaranteed root cause diagnoses. Developers must verify the findings before taking action. This is an MVP that can be extended with pull request analysis, regression detection, and feedback from resolved incidents. 💬 What would you add to this AI incident investigator? Technologies Used n8n, Sentry, GitHub API, PostgreSQL, Slack, AI Agents, workflow automation, incident management, observability, root cause analysis. Keywords Sentry automation, AI incident investigation, n8n AI agent, automated root cause analysis, production incident management, Sentry webhook, GitHub commit analysis, DevOps automation, PostgreSQL incident tracking, AI-powered debugging, error monitoring, observability automation. #Sentry #n8n #AIAutomation #DevOps #GitHub