Amazon Quick is adding an AI-powered catalog workflow meant to shorten the setup work behind trusted analytics. The new Agentic Catalog Experience lets data curators describe a business need in natural language, then uses upstream catalog context to suggest and create relevant datasets and topics.
The preview supports AWS Glue Data Catalog and Databricks Unity Catalog. Amazon says the Quick Agent can summarize catalog contents, surface useful tables and relationships, assess metadata readiness, and inherit descriptions, semantics, and governance context instead of forcing teams to rebuild that information by hand.
The practical target is the last mile between well-maintained data catalogs and business users who expect natural-language answers or reliable dashboards. If table meanings, relationships, and governance rules do not travel with the data, text-to-SQL systems can produce answers that look fluent but lack the right business context.
The feature is still in preview, so teams will need to evaluate coverage and accuracy before relying on it in production. Its main promise is reducing the manual translation between catalog work and analytics experiences.