Reduce the difficulty of building the knowledge base. Instead of manually understanding and classifying documents, it now involves large models reading massive documents, supporting the input of knowledge in multiple formats and from various sources. The input of knowledge is efficient and direct. The construction of the knowledge base can be initiated quickly. 

Lower the threshold for knowledge acquisition. Users shift from pre-learning and using precise words for searching to inputting through natural language and conducting accurate information retrieval based on intentions. This reduces the need for learning the organization system of the knowledge base and the requirement for precise word matching. Users initiate inquiries from the perspective of business scenarios. 

Improve the efficiency of knowledge acquisition. From the system returning a large amount of text mixed with useless information, to the rapid summarization function, it significantly shortens the time for knowledge acquisition, helping customers obtain the required information more quickly and improving work efficiency. Relevant knowledge acquisition effectively enhances the cognitive level of personnel.