Amazon Quick Research is a new tool designed to simplify the integration of heterogeneous data sources for rare cancer research. Traditionally, researchers face significant challenges in combining genomic sequencing data, clinical trial registries, and peer-reviewed literature, often requiring custom ETL pipelines and manual schema reconciliation—a process that can take weeks before analysis begins. Amazon Quick Research addresses this by providing a unified research environment that ingests structured and unstructured data from multiple sources, including publicly available biomedical databases such as PubMed, and applies large language model-driven synthesis to generate cited, versioned research reports. The tool supports end-to-end workflows, from defining a research objective to iterating on results using a revision and versioning system. It allows users to create Spaces, which are logical containers for organizing up to 10,000 files, and connect them with external data sources for comprehensive analysis. The platform also enables users to generate structured reports with inline citations, exportable in PDF or Word formats, and tailor outputs for different audiences with summary variants. *Source: [awsml](https://aws.amazon.com/blogs/machine-learning/transforming-rare-cancer-research-with-amazon-quick-integrating-biomedical-databases-for-breakthrough-discoveries/)*