Amazon Quick announces autonomous agents, multi-dataset analytics, and redesigned activity feed

Today, AWS announces multiple new features for Amazon Quick, including autonomous agents, multi-dataset analytics capabilities, and a redesigned activity feed. Amazon Quick is the AI assistant that connects to popular business applications and learns user workflows. These new capabilities enable Quick to handle recurring tasks continuously while providing unified analytics across multiple data sources.

With autonomous agents, users can describe tasks in natural language and set granular autonomy levels—from step-by-step approval to broad goal-based execution. Agents operate continuously to automate workflows like following up on stalled deals, summarizing regulatory changes, and processing purchase orders, eliminating manual repetitive work and notification overload. The new multi-dataset analytics feature enables users to query across data sources including Snowflake and relational databases using natural language, without requiring technical data preparation or pre-joining datasets. Quick inherits semantic intelligence from existing data catalogs such as AWS Glue, Databricks Unity Catalog, and Collibra, while enforcing security through identity propagation that respects existing permissions.

The redesigned activity feed provides a personalized, conversational interface where users can prioritize updates using thumbs up/down feedback, reply to emails and Slack messages, and approve requests directly—all without switching between applications. Users can also share Quick applications as public websites, extending collaboration capabilities beyond their organization.

To learn more about these new Amazon Quick capabilities, including autonomous agents, multi-dataset analytics., and redesigned activity feed, read the launch blog. You can create an account for free and get started in minutes at aws.com/quick.