A financial services company runs a customer-facing chat assistant on Amazon Bedrock using Anthropic Claude. During market hours, users complain that responses feel sluggish, and the product team wants to reduce time-to-first-token and overall response latency for interactive turns. The engineering team already uses streaming. They are willing to accept a higher per-token cost in exchange for faster inference, but they must not change the model family or introduce a separate fine-tuned model. Which approach best meets these requirements with the least operational overhead?