Enabling conversational data discovery with LLMs at Grab

This post details the evolution of Grab's data discovery platform, Hubble, by integrating LLMs to create HubbleIQ. The technical contributions include: 1. Enhancing Elasticsearch for exact, partial, and inexact search queries by tagging P80 tables, boosting relevant schemas, hiding irrelevant datasets, deboosting deprecated tables, improving the search UI, adding tags, and boosting certified tables, resulting in a 12 percentage point increase in click-through rate to 94%. 2. Building a context store for HubbleIQ by developing a GPT-4 based documentation generation engine that uses table schemas and sample data, increasing documentation coverage for P80 tables by 70 percentage points to ~90%. 3. Launching HubbleIQ by integrating Hubble with Glean, creating a bot using Glean Apps with a custom system prompt, and integrating it into Hubble search and Slack. This has reduced data discovery time and improved user satisfaction.