Overview
Give AI agents the context to find, understand, and use your data.
A question like "Why did revenue drop?" needs more than access to tables. An agent needs to know which revenue metric to use, what it includes, and where the underlying data comes from.
Semantic Catalog brings business definitions, documentation, ownership, and lineage into one searchable place, connected to your semantic layer.
- Find the right data. Discover metrics and datasets using business language.
- Understand how to use it. Retrieve definitions, examples, and guidance for the question at hand.
- Trace where it comes from. Follow lineage from metrics to source data and transformations to investigate changes and understand dependencies.
- Govern shared knowledge. Assign owners, review definitions, and publish approved context so agents use knowledge your team trusts.
Your Semantic Layer defines how metrics are calculated. Semantic Catalog adds the context to choose those metrics, understand their meaning, and trace their sources.
Together, they help agents move from a business question to an answer people can understand and verify.
How it works
Start by ingesting dbt and LookML projects into the catalog. Then search it and trace lineage through it.