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Explore a 32-minute conference talk showcasing how a Financial/Insurance company implemented a Retrieval Augmented Generation (RAG) system to enhance customer service efficiency. Gain insights into the RAG architecture and learn how Databricks was utilized to build a robust data pipeline for indexing content and collecting user feedback. Discover innovations such as multi-stage content chunking, advanced search retrieval techniques, and an evaluation framework for optimization. Understand how the feedback loop using Databricks workflow improves the RAG implementation. Learn about the unique orchestration layer that accelerates Generative AI use cases. Grasp how Generative AI can transform customer service operations with strategies for efficiency and automation. Apply these learnings to any customer service organization striving for operational excellence. Presented by Gen Li, Lead Data Engineer, and Peter Landis, Principal Engineer from Northwestern Mutual. Access additional resources including the LLM Compact Guide and Big Book of MLOps. Connect with Databricks through their website and various social media platforms for further engagement.
