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RAG-Powered Intelligent Customer Service on the Lakehouse

Builds a knowledge Q&A system on large language models (LLMs) and lakehouse technology. It intelligently understands questions from enterprise staff and retrieves relevant answers from massive volumes of uploaded professional and technical documents. With retrieval-augmented generation (RAG), the system efficiently retrieves relevant information and combines it with the language model to produce accurate, professional answers, improving enterprise knowledge management and problem-solving efficiency

RAG-Powered Intelligent Expert System

LakeSoul provides a native Python interface with support for mainstream AI frameworks such as PyTorch for direct data access, training, and inference. It also supports large-model training and RAG applications

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AI Expert Consultation

Case Study

Expert Consultation Pain Points at a New Energy Vehicle Company

· Build an engineering knowledge Q&A system based on LLMs and the lakehouse that intelligently understands questions from engineering management staff across automotive industry organizations

· Retrieve relevant answers from professional engineering and technical documents uploaded by evaluation experts

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