Unity Catalog Pages: a governed home for your business knowledge in Genie Ontology

Every AI agent is only as good as the context it is grounded in. Ask an agent a question about revenue, active customers, or churn, and the quality of the answer depends entirely on whether the agent understands what those words mean inside your business.

In many organizations, that meaning does not live in one place. It is scattered across Slack threads, Confluence pages, spreadsheets, and the tribal knowledge in a few people's heads, and the same term is often defined three different ways by three different teams. So when an agent hits an ambiguous concept, it does what LLMs do best: it guesses confidently, even when it is wrong. This gap is one of the biggest barriers to enterprises trusting AI with real business questions.

This is the problem Genie Ontology was built to solve. Genie Ontology is Databricks’ enterprise context layer for all AI: it automatically learns how your business works by extracting knowledge from your dashboards, queries, tables, pipelines, and connected apps, and organizes it into a living graph that tells Genie and other agents where to look and what to trust.

That automatic understanding covers an enormous amount of ground on its own. But some concepts are too important to leave to inference. When "completed trip" or "active customer" has to be exactly right, you want your own experts to define it once, in a place every person and every agent can rely on. Unity Catalog Pages fill this exact gap. As the newest piece of Unity Catalog semantics, the human-curated layer of Genie Ontology, Pages provide a governed home where your data stewards, with the help of Genie Code, can now define the authoritative meaning of a concept, and Genie treats that definition as the source of truth.