Amazon Quick Launches Agentic Catalog Experience with AI-Powered Workflow

Amazon Quick is now offering an AI-powered workflow called Agentic Catalog Experience that helps data curators define their context boundary, inherit upstream semantics, and enable end users for grounded Q&A and trusted dashboards at scale.

The Agentic Catalog Experience aims to bridge the gap between upstream data catalogs and downstream analytics tools like Amazon Quick. Data teams have invested heavily in platforms such as AWS Glue Data Catalog, Databricks Unity Catalog, Snowflake Horizon, Collibra, and dbt, but still face challenges in enabling end users for production-ready AI and trusted dashboards.

The Agentic Catalog Experience uses natural language asset discovery to help curators find the right upstream assets that are curated and approved for reporting. The Quick Agent searches across the entire catalog to surface the most relevant tables instantly using all available metadata, including business descriptions, tags, classifications, quality scores, and glossary terms.

The Agentic Catalog Experience creates catalog representations (Datasets) at scale in a single guided workflow, inheriting targeted metadata from the upstream catalog into the assets it creates. The Quick Agent carries forward table and column definitions to Datasets and primary and foreign key relationships to Topics, making it easier for end users to create dashboards and ask questions.