Every finance professional knows the drill. Monday morning arrives, and your Financial Planning and Analysis (FP&A) team disappears into data compilation. They pull numbers from multiple systems, reconcile sources, build charts, and write commentary. All to answer a question that should be straightforward: what happened with revenue last week, and why?

Across AWS Finance, teams were spending hundreds of hours a month on exactly this kind of work. Not analysis. Not strategy. Getting the data ready so the real work could begin.

Amazon Quick is a generative AI assistant that connects across all your enterprise data and applications, so business users can search, analyze, and take action through natural language. It handles the complexity of querying millions of rows, running advanced analytics, and automating recurring workflows so your team doesn’t need to.

In this post, we show how AWS Finance used chat agents and Flows in Quick to transform two of their most time-consuming workflows.

Use case 1: Scenario modeling and risk analysis across the strategic portfolio