Development for an AI Agent-Powered System for Intelligent Quality Management Documentation

Abstract

The management of documentation within Quality Management Systems (QMS), particularly for standards like ISO 9001:2015, is a critical yet often inefficient process. Traditional methods are manual, time-consuming, and prone to human error, hindering organizational compliance and continuous improvement. This paper presents the design and implementation of an intelligent system powered by an AI Agent to automate and enhance the evaluation of QMS documents. The system employs a three-tier architecture comprising a ReactJS frontend, an ASP.NET Core backend, and a dedicated AI service built with Python and FastAPI. The core of the system is an AI Agent that leverages a fine-tuned Large Language Model (LLM), Vistral-7B-Chat, optimized for the Vietnamese language and the specific context of ISO 9001. The model was fine-tuned using Low-Rank Adaptation (LoRA) on a specialized dataset of compliance criteria. The developed prototype enables users to upload documents, receive automated compliance assessments against ISO 9001 clauses, and interact with a specialized chatbot for queries. The results demonstrate the system's capability to accurately identify compliance gaps and provide actionable feedback, showcasing the significant potential of AI Agents in modernizing quality management processes.

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