An AlphaSense case study: scaling AI on enterprise data with dbt-first governance and context from Euno

AlphaSense's objective for 2026: deploy AI on top of core data to drive faster decisions across data and business teams. Plugging agents into complex systems as-is didn't work. Hallucinations, inconsistencies, and a manual governance burden couldn't keep pace. Every AI outcome needed to trace back to it source. This session shows how AlphaSense paired dbt with Euno's governance automations to unify lineage, ownership, and semantic context across Snowflake, dbt, Fivetran, Tableau, and more, then surfaced that trusted context directly into the agents its teams run, including Claude and Cursor. Walk away with a pattern for grounding your own AI agents in governed, explainable data.