A publishing team is building a process that must take a submitted article, retrieve related fact-check sources, summarize them, then translate the summary into three languages, all before a human editor reviews it. Which Azure AI Foundry tool should they use to design and orchestrate this multi-step process visually?
Select an answer to reveal the explanation.
Short Explanation
When you need retrieval, summarization, and translation to run in sequence, you want each stage visible and testable. Prompt flow lets you connect those steps as nodes in one executable flow, so you can trace and fix each stage. Safety panels or model comparison views won't build that chain.
Full Explanation
Prompt flow is the correct answer because it lets the team lay out retrieval, summarization, and translation as distinct connected nodes, each with its own inputs and outputs, so the process runs as one traceable, executable pipeline and each stage can be tested or swapped independently. The content safety configuration panel is incorrect because it screens generated text for policy violations; it has no mechanism for chaining retrieval, summarization, and translation steps together. Using one chat completion call with one long system message covering all four steps is incorrect because it removes any visibility into which stage produced bad output, makes debugging translation errors versus summarization errors nearly impossible, and is fragile if any one step needs different handling. The model catalog's comparison view is incorrect because it exists to help choose between candidate models on metrics like cost or accuracy, not to build or run such multi-step content pipelines. Prompt flow is purpose-built for exactly this kind of staged, multi-step orchestration with clear boundaries between each operation.