The chapter details the company's shift towards integrating LLMs, explaining their architecture's efficiency in importing and processing user emails. It discusses the choice of open-source embedding models for cost efficiency and performance in handling large amounts of data. The complexities of managing large data in vector databases, the architecture of the AI search system RAG, and the future optimization of embedding models and database management are also explored.

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