Databricks + Atlan: Building the AI-Native Enterprise, Together
See how Databricks Genie, grounded in Atlan's context layer, powers AI agents that reason from certified data, enforce governance, and explain every output.
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About this Session
At enterprise scale, AI agents multiply faster than shared context does, leaving every agent reasoning from a different version of the truth. The result: conflicting answers, eroding trust, and AI that gets harder to govern as it scales.
Databricks and Atlan solve this together. Databricks Genie provides the intelligence layer: querying the data estate, reasoning over it, acting on what it finds. Atlan provides the context Genie needs: semantics, quality signals, and governance policies that make those answers trustworthy and explainable.
Join the Databricks and Atlan teams on May 20 to see how to build that context layer from the ground up.
What you'll see
01
Genie without context vs. with context
Same business question answered twice: first by a Genie Space reasoning over raw tables and columns, then by the same Genie logic inside an Agent Brick with Atlan's MCP server and context repositories wired in. Same intelligence, see what context changes about the answer.
02
Engineering Genie-ready context
See how Atlan's Context Engineering Studio turns raw Databricks assets into metric views, Genie Space configurations, and semantic relationships, all generated from the enterprise data graph instead of hand-written prompt hacks.
03
Governance and quality in Genie's decision loop
See how Atlan's policies and Data Quality Studio checks flow into Genie as constraints and signals, so agents can prefer trusted data products, respect access rules, and explain where every number came from.
04
From POC to production grade agents
Learn a concrete rollout pattern for Databricks + Atlan: from wiring connectors to deploying governed Agent Bricks, so platform teams can move from POC to production-grade agents faster, without trading off safety for speed.
Upcoming Sessions
Most teams have data. What they're missing is the layer that makes AI trustworthy. In this 45-minute live session, you'll see Atlan's context layer in action — from enriching raw data assets to engineering a semantic model, running evals, and watching an AI analyst answer business questions correctly.
Atlan creates the governed policy context. Immuta enforces the right access at the source. Watch the complete governed access flow live: from discovery in Atlan to dynamic provisioning by Immuta, and the same pattern extended to AI agents.
The only proven way to create context
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