Question 1

What is the key difference between a RAG knowledge base and traditional keyword search?

Accepted Answer

Traditional search relies on keyword matching, while RAG (Retrieval-Augmented Generation) combines semantic vector retrieval with large language models. Users ask in natural language, the system retrieves relevant document chunks, and the LLM generates accurate answers with source citations. Answer accuracy typically exceeds 95%, and every response is traceable to its source, fundamentally eliminating AI hallucinations.

Question 2

What materials does a company need to provide for AI video batch generation?

Accepted Answer

Typically required: brand character or digital avatar assets (for consistency training), script templates or topic inputs (AI can auto-generate scripts), and brand guidelines (colors, logo, etc.). After the initial character training session, videos on different topics can be batch-produced without providing materials each time.

Question 3

Which enterprise systems can the AI business assistant integrate with?

Accepted Answer

XiCheng Digital's AI assistant uses an Agent architecture and integrates with ERP, CRM, OA approval workflows, and BI platforms. It also supports WeCom, DingTalk, and Feishu, so employees continue using their existing tools without workflow disruption.

Question 4

How does the AI medical recommendation system protect patient privacy?

Accepted Answer

The system uses a private encryption protocol with all patient data processed locally — nothing is uploaded to third-party clouds. It supports on-premise deployment to meet healthcare data compliance requirements, with data masking and access control to protect sensitive information.

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RAG Enterprise Knowledge Base

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AI Video Batch Generation

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AI Medical Recommendation System

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Enterprise AI Assistant

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