Fine-tune a search agent with multi-turn RL on Amazon SageMaker AI
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Fine-tuning teaches a small search agent your tools and environment, giving it the reliability of a frontier model at lower latency and cost. In this post, we fine-tune an LLM-powered search agent with multi-turn reinforcement learning (MTRL) on Amazon SageMaker AI and share the gains we measured in retrieval quality and reliability.
Search agents powered by large language models (LLMs) are transforming how enterprises retrieve information. Rather than requiring users to craft the perfect query, a search agent autonomously decides what to search for, which retrieval strategy to use, and when to stop searching. It does this across multiple rounds of interaction, refining its approach based on what it has already retrieved. However, getting this multi-step behavior to work well is hard. No base model arrives knowing your…
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