Developer Builds AI System to Unify GitHub Data Into Queryable Knowledge Graph

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A developer has created an open-source AI Operating System for organizations that aggregates scattered GitHub data — including commits, pull requests, and issues — into a connected graph database. The tool allows teams to query organizational knowledge in plain language, such as identifying who modified a file or which issues were resolved in a release. Built with Python, FastAPI, Neo4j, and Docker, the system's core technical challenge was linking the GitHub API to Neo4j in a queryable structure. The project is aimed at helping teams with common pain points like onboarding new engineers and investigating incidents. The source code is publicly available on GitHub, with a live demo hosted on Netlify.

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