Learn how to optimize Large Language Models (LLMs) in the insurance industry using DSPy, a framework that automates prompt and weight optimization to replace manual tuning processes. Discover how traditional LLM deployment challenges in insurance—including extensive prompt engineering and error-prone fine-tuning—can be overcome through DSPy's automated optimization approach. Explore practical applications of LLM technology in insurance operations, from claims management assistance to coverage analysis tools, while understanding how to build efficient ML infrastructure that enables data scientists to deploy models reliably at scale. Gain insights from real-world implementation experience at AXA, one of the world's largest insurers, and learn about innovative approaches to creating LLM-based solutions for customer service and claims processing in the insurance sector.