The study introduces ZenDB, a new system that couples semantic structure awareness with Large Language Models to perform document analytics more efficiently. - System design: ZenDB extracts document structures and supports SQL queries, significantly reducing the computational costs associated with traditional document query methods. - Performance evaluation: Demonstrates a 30% cost reduction and improvements in accuracy and precision over existing LLM-based methods. - Innovative features: Highlights the novel integration of semantic structural analysis with advanced language models. - Industrial applicability: The solution is poised to revolutionize industries where large scale document management is critical. - Future prospects: Offers a detailed look at how integrating traditional databases with advanced AI can lead to substantial performance enhancements. Opinion: ZenDB’s approach to document analytics showcases a significant advance in combining AI with database technologies, promising to redefine the paradigms of data management and analytics in numerous sectors.