Launching UI for generative AI inference recommendations in Amazon SageMaker AI

Amazon SageMaker AI Studio launches a UI for generative AI inference recommendations, enabling teams to optimize model deployments without deep infrastructure expertise.

• Preset use-case profiles (Interact, Generate, Summarize, Custom) capture common traffic patterns for workload configuration
• Select optimization goals: minimize latency, maximize throughput, or minimize cost to shape recommendations
• Support multiple model sources: SageMaker JumpStart, Amazon S3, Model Registry, or existing deployments
• Visual comparison of performance metrics including time-to-first-token, inter-token latency, throughput, and cost
• One-click deployment of recommended configurations to production endpoints
• Guided end-to-end workflow from model selection through deployment validation

The console experience democratizes infrastructure optimization, allowing ML engineers and technical leaders to make data-driven deployment decisions and move from model selection to production-ready configuration in minutes.