When Miro’s data team pointed AI agents directly at its Snowflake environment, the agents got the wrong answer more than 65% of the time. The problem wasn’t the model — it was context. With more than 10,000 tables and no semantic layer to guide routing, the agents had no way to know which data assets matched which business questions.DataHub is releasing a context intelligence layer Thursday that mines existing SQL query history to build a semantic index — and exposes it to agents via MCP, LangChain, Google’s Agent Development Kit and CrewAI. The company calls it Context Intelligence, and it’s built on the same query-log infrastructure DataHub has used for lineage tracking in production deployments worldwide.The company was founded by the team that built DataHub as an open source project at LinkedIn, where co-founder and CTO Shirshanka Das led data infrastructure for nearly 11 years. The open source project now has more than 15,000 contributors and 3,000 production deployments worldwide.”For the first time, enterprises can turn years of analyst query history into a living, retrievable knowledge base where agents stop hallucinating joins because they have access to the joins that have worked before, validated by the people who ran them,” Shirshanka Das, co-founder and CTO of DataHub, told VentureBeat in an exclusive interview.Why query history beats raw schema for agent routingDataHub began as a metadata management project at LinkedIn, built to solve two problems simultaneously: making data easy to find and use across the organization while ensuring it was only used for the right reasons. Das open-sourced …
