Databricks removes the knowledge barrier with Glean's unified search and AI assistant
Databricks employees wasted time hunting for information across fragmented tools because existing search engines failed to surface relevant results.
Prior search engines at Databricks failed on relevance — they did not surface the right results when employees searched across systems.
Glean gave Databricks a unified intranet search that delivers relevant information instantly, and an AI-powered assistant that retrieves deeper insights through natural conversation.
Frequently asked questions
What did this team achieve with this AI workflow?
Glean gave Databricks a unified intranet search that delivers relevant information instantly, and an AI-powered assistant that retrieves deeper insights through natural conversation.
What tools did this team use?
Glean, Google Workspace, Atlassian, Salesforce, Slack.
What results were reported?
Information retrieval speed: find what they need right away; Employee productivity: Spend less time searching and more time working productively (source-reported, not independently verified).
What failed first in this deployment?
Prior search engines at Databricks failed on relevance — they did not surface the right results when employees searched across systems.
How is this back office ops AI workflow structured?
Employee seeks information → Glean unified search → AI assistant for deeper insights.