Closing the context gap: Cribl’s blueprint for trusted AI with dbt + Omni

🌎 Global Friendly Sessions on January 13th & 14th

Everyone wants AI-driven analytics, but few trust the answers. The problem isn't the AI model; it’s the Context Gap between your data warehouse and the end user. This gap is a disconnect between what a data warehouse can technically answer and the business context, intent, and assumptions the questioner brings with them. When that context is lost, AI outputs are fast, confident, and wrong.

Join us to see how modern teams are closing this gap. Priya Gupta, Head of Data at Cribl, will share a practical architecture for treating Omni and the dbt Platform as the "Structured Context" engines for the entire business, unifying the lifecycle from code to conversational AI.

In this session, you will learn how to:

• Deploy Agentic Modeling: Use AI agents to "prompt-engineer" dbt descriptions and lineage at scale, automating the creation of a rich Semantic Layer.
• Synchronize the Development Lifecycle: Stop pushing breaking changes. See a workflow where development happens in dbt and validation happens instantly in Omni—catching errors before merge.

Plus, a live demo of the "AI Context Loop." We will go under the hood to show:

• Surfacing Metadata: How connecting MCP servers makes your chatbot an expert in both dbt metadata and Omni analytics.
• The Feedback Loop: How to use AI-generated answers to audit and improve your upstream dbt documentation, turning user questions into a tool for better governance.