September 15-18
The Cosmopolitan
Las Vegas

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

Breakout sessionPowering AI-ready dataIntermediateBusiness leaders and executivesData leadersAll industries
Okta set a clear objective for 2026: deploy AI on top of core data to drive faster decisions across both data and business teams.

But plugging agents into complex systems as-is didn’t work: hallucinations, inconsistencies, and a growing burden of manual governance that couldn’t keep up with the speed of AI. At the same time, Okta required every AI outcome to be fully explainable, down to the source data behind each decision.

We’ll show how Okta took a different approach:

By leveraging dbt™ plus Euno’s governance automations, Okta collects and reconciles context across its data ecosystem: Snowflake, dbt, Fivetran, Tableau, and more. From lineage, usage and ownership to semantic resolution and institutional knowledge encoding, that trusted context is then surfaced at runtime directly into agents they use, like Claude.

This defines a new standard for enterprise AI, grounded in governed data that dbt practices enable, and the full stack context Euno provides for reliable results.
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