Uber has unveiled QueryGPT, an AI-powered tool designed to transform natural language inputs into optimised SQL queries, significantly enhancing data accessibility and operational efficiency.

This innovative system leverages Large Language Models (LLMs), vector databases, and retrieval-augmented generation (RAG) to automate dataset selection, query structuring, and optimisation.

Traditionally, Uber’s teams faced challenges in writing SQL queries, a process that demanded a deep understanding of table schemas and manual query construction, often taking over 10 minutes per query. With QueryGPT, this time has been reduced to just 3 minutes, streamlining data analysis and decision-making processes. The tool was initially developed during Uber’s Generative AI Hackdays in May 2023 and has since evolved to include components like Workspaces, Intent Agents, Table Agents, and Column Prune Agents, all aimed at improving accuracy, efficiency, and cost-effectiveness.

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Since its implementation, QueryGPT has saved Uber an estimated 140,000 hours per month in query-writing efforts, allowing teams to focus more on deriving actionable insights from data. This development underscores Uber’s commitment to leveraging cutting-edge AI technologies to enhance internal operations and data accessibility.

For organisations seeking similar advancements in SQL query generation, platforms like Sequel.sh offer AI-driven solutions that convert natural language queries into SQL, facilitating efficient data analysis and visualisation without the need for extensive SQL knowledge.

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