SQL is a vital tool used daily by engineers, operations managers, and data scientists at Uber to access and manipulate terabytes of data. Crafting these queries not only requires a solid understanding of SQL syntax, but also deep knowledge of how our internal data models represent business concepts. QueryGPT aims to bridge this gap, enabling users to generate SQL queries through natural language prompts, thereby significantly enhancing productivity.

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QueryGPT is a tool developed by Uber to generate SQL queries from natural language, significantly improving productivity by reducing query authoring time. Utilizing large language models, vector databases, and similarity search, QueryGPT handles about 1.2 million interactive queries monthly. Its architecture includes multiple agents to refine accuracy in interpreting user prompts and selecting relevant data tables. Despite challenges such as handling large schemas and reducing hallucinations, continuous improvements have been made. The tool democratizes data access, making insights more accessible across different teams at Uber.

QueryGPT – Natural Language to SQL Using Generative AI