Amazon Quick expands capabilities with natural language data analysis and AI agents

Amazon Quick is evolving from a simple conversational AI into an agentic tool capable of executing complex workflows and analyzing data through natural language.

One key feature, Dataset Q&A, allows users to perform exploratory data analysis without pre-configuring dashboards. By selecting specific datasets, users can ask questions in natural language to receive answers in the form of text, tables, or graphs. The system can query various sources, including Amazon Redshift, Athena, and S3, and even incorporate local files like CSVs or PDFs. Users can also verify the logic behind AI-generated answers by reviewing the underlying queries and filters.

Beyond data analysis, Amazon Quick is moving toward the role of an AI agent. It can connect web research, official documentation, and personal writing styles to complete multi-step tasks, such as drafting articles, generating images, and saving files. Through the use of knowledge graphs, the tool can remember relationships between people, projects, and documents, allowing it to perform follow-up tasks without repetitive instructions. Users can also automate these workflows by scheduling tasks to run at specific times.