Jessica Eurich

What if your Databricks apps, agents, and dashboards could do more than return metrics — and actually understand the business context behind them? In this session, we’ll show how Genie Code and Glean MCP work together to combine governed Databricks data with enterprise context from docs, tickets, Slack, CRM, and email. You’ll see how Genie Code powers trusted queries on Databricks, while Glean MCP brings in the surrounding context that makes answers more complete, explainable, and actionable. We’ll walk through how Glean fits into Genie through MCP patterns, how queries stay grounded in Databricks governance, and how teams can move from a correct query to a trusted, contextual answer in the UI they already use.

Data only drives real business value when it is made actionable and accessible to everyone who needs it. See how customers are turning Databricks investments into day-to-day business value with Glean by bringing governed data together with the enterprise context needed to make it actionable. We’ll share two examples: Real estate platform Zillow’s employee-facing HR agent, which helps answer workforce questions in Slack using trusted company context and people data, and a leading automotive manufacturer’s use of Glean AI to support engineering and product workflows with easier access to structured data and company knowledge. The result: Faster self-service, fewer bottlenecks for technical teams, and more useful AI in the flow of work.

This session shows how Glean, the Work AI platform, connects to Snowflake CoCo via MCP to bring enterprise context directly into Snowflake builders’ dev workflows. We cover the value of Glean and Snowflake for conversational analytics, then demo Glean’s integration with Snowflake CoCo using a finance schema spanning subscriptions, customers, invoices and MRR snapshots. We’ll show how a semantic view optimizer in Snowflake CoCo inspects DDL, searches finance SOPs and Slack via Glean, refines metrics such as active customers and churn, and then compares the original and optimized views in Snowflake Cortex Analyst.