Sponsored by: ThoughtSpot | What AI Agents Get Wrong and How Semantics Fixes It

AI agents are only as good as the context they're given. Yet most enterprise AI stacks leave agents to guess what "revenue," "active customer," or "churn" actually means-producing answers that are confident but wrong.

In this session, we'll show how a governed, agentic semantic layer becomes the contract between your data and every AI agent in your stack. You'll see how human-verified business definitions, deterministic SQL, and purpose-built AI context work together in ThoughtSpot to make every agent response accurate, traceable, and trusted by business users-not just data engineers.

We'll walk through a live integration between our semantic layer and Databricks Unity Catalog Metric Views, demonstrating a two-way semantic sync that brings governed business logic directly into your AI-native workflows. Whether you're building analytics agents, enterprise copilots, or data products, you'll leave with a replicable pattern for grounding AI in your organization's source of truth.