How we built an internal data analytics agent

GitHub has detailed its development of Qubot, an internal analytics agent that lets employees query company data using natural language. Powered by GitHub Copilot, Qubot translates plain-English questions into SQL queries against internal databases. The engineering team shared key takeaways from the project, including the necessity of maintaining comprehensive data schema documentation to guide the AI, implementing robust security controls to restrict data access, and establishing feedback mechanisms for users to correct inaccurate results. They also emphasized the importance of handling ambiguous queries gracefully, often by asking clarifying questions. The project illustrates a practical path for organizations to build custom AI-driven data interfaces without external services, leveraging existing LLMs and careful prompt engineering. For developers creating similar internal tools, the post highlights that data quality and user trust are as critical as model performance.