DataHub May Town Hall

​Context to Action
Power Agents. Ship Outcomes. With DataHub.
Production stories from Grab, dltHub, and iFood

​The context layer is no longer the new idea — it's the foundation teams are building production AI on. This month, hear from the teams putting DataHub at the center of that shift.

​What we'll cover:

• ​Grab Deep Dive. George Hurley and Aezo Teo on Grab's evolution of DataHub from a metadata store for human analysts into an agentic context engine that powers their next generation of AI agents. A look at the journey of building this context store and the lessons learned from scaling AI at Grab.

• ​dltHub Spotlight. Elvis Kahoro on agentic data engineering in Python. An end-to-end workflow using Claude Code to pull data from external sources, generate an ingestion pipeline, transform the dataset, and publish a validated pipeline to production.

• ​iFood Spotlight. Alexandre Miyazaki on iFood's journey from 9,000+ personal AI agents to consolidated "Super Agents" — and putting DataHub's Analytics Agent to work at iFood.

​Plus the latest from the DataHub team on our newest OSS release and new connectors.

​Speakers:

• ​George Hurley, Grab

• ​Aezo Teo, Grab

• ​Elvis Kahoro, dltHub

• ​Alexandre Miyazaki, iFood

• ​Maggie Hays, DataHub

​Whether you're building context engines, scaling agents, or wiring up the data plumbing that makes both possible – this town hall meets you where production starts.

​See you there!

​Join the conversation in our Slack community — we'll be hanging out there during and after the event, and it's the best place to follow up on speaker Q&A and connect with folks building on DataHub: https://datahub.com/slack

​Building with DataHub? Star us on GitHub to follow along with the project: https://github.com/datahub-project/datahub