Question

Your team is building a generative application in Azure AI Foundry that summarizes long legal contracts. Business stakeholders require the highest possible summarization quality and are willing to accept higher per-token cost and slower response times, since summaries run as scheduled overnight batch jobs rather than interactively. You must choose a deployment approach in Foundry that best fits this workload. Which approach should you select?

Accepted Answer

Deploy a large frontier reasoning-capable model on a standard (pay-as-you-go) deployment and run the summaries as an offline batch job.

Answer

Deploy a small language model (SLM) optimized for edge latency to reduce cost per summary.

Answer

Configure a model router to dynamically pick the cheapest model per request to minimize spend.

Answer

Deploy a multimodal vision model so contract images and text can both be processed.