Intelligent RAG enhanced large model auxiliary writing system

The intelligent RAG-enhanced large-model assisted writing system, with its seven-layer fusion architecture, solves the systemic defects of large-scale language models in high-professional-barrier writing scenarios, and achieves high-quality, compliant, and interpretable text generation and proofreading, adapting to the writing needs of different professional scenarios.

CN121638211APending Publication Date: 2026-03-10INSPUR QILU SOFTWARE IND
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Patent Information

Application Number
CN202511728688.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-24
Publication Date
2026-03-10

AI Technical Summary

Technical Problem

Existing large-scale language models (LLMs) suffer from systemic defects in writing scenarios with high professional barriers and strong compliance requirements, such as knowledge blind spots, single-model bottlenecks, zero verification mechanisms, knowledge lag, scenario insensitivity, security and compliance risks, and industry adaptation gaps. These defects lead to inaccurate generated content, logical drift, high proofreading costs, and an inability to quickly update and adapt to different scenarios.

Method used

The intelligent RAG-enhanced large model-assisted writing system adopts a seven-layer fusion architecture, including an interface and user layer, a service layer, a platform layer, a large model layer, a data layer, an interpretability and security layer, and an infrastructure layer. Through industry-adaptive parsing, hybrid retrieval, RAG enhancement, multi-agent scheduling, and temporal knowledge graph verification, it achieves a dynamic, reliable, and scalable writing enhancement framework.

Benefits of technology

It solves the problems of industry context mismatch, terminology drift and insufficient word rigor in existing technologies, and realizes high-quality and compliant text generation and proofreading. It reduces the cost of manual proofreading, improves the interpretability and security of generated content, and adapts to the writing needs of different professional scenarios.

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Abstract

The invention discloses an intelligent RAG enhanced large model auxiliary writing system, and relates to the technical field of artificial intelligence auxiliary writing. In order to overcome the defects of an existing writing auxiliary tool, the adopted scheme comprises an interface and user layer for receiving a writing demand and redisplaying a generation result; the service layer is used for deploying three types of intelligent agents including writing, interactive writing enhancement and checking; the platform layer is used for carrying out industry adaptation analysis, mixed retrieval and RAG enhancement on writing demands and then sending the writing demands to the large model layer; three intelligent agents of writing, interactive writing enhancement and checking are called in sequence based on the output of the large model layer, and then a text is redisplayed to the interface and user layer after fact accuracy verification is completed through a tense knowledge graph; the data layer is used for providing a multi-type data storage system; the large model layer outputs a paragraph-level text and a reference index based on a writing large model, the paragraph-level text is returned to the platform layer, and reference index information is fed back to the interpretability and security layer for tracing; and the infrastructure layer is used for providing bottom layer resource support for each layer.
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