Multi-LLM routing strategies for generative AI applications on AWS

This article provides a comprehensive overview of multi-LLM routing strategies for generative AI applications on AWS, exploring how organizations can effectively use multiple large language models to address diverse task requirements.

• Common multi-LLM application scenarios include:
  • Multiple task types
  • Different task complexity levels
  • Multiple task domains
  • SaaS applications with tenant tiering
• Two primary routing strategies are discussed:
  • Static routing (using dedicated UI components)
  • Dynamic routing (using classification techniques)
• Dynamic routing approaches include:
  • LLM-assisted routing
  • Semantic routing
  • Hybrid routing
• Implementation options range from Amazon Bedrock's Intelligent Prompt Routing to custom solutions using AWS services like Lambda and API Gateway

The article emphasizes that choosing the right routing strategy depends on factors like model hosting, operational overhead, and desired routing logic control.