Manufacturing high quality audits are pivotal for guaranteeing excessive product requirements in mass manufacturing environments. Conventional auditing processes, nevertheless, are labor-intensive and closely reliant on human experience, posing challenges in sustaining transparency, accountability, and steady enchancment throughout advanced international provide chains. To handle these challenges, we suggest a sensible audit system empowered by giant language fashions (LLMs). Our method introduces three key improvements: a dynamic danger evaluation mannequin that streamlines audit procedures and optimizes useful resource allocation; a producing compliance copilot that enhances information processing, retrieval, and analysis for a self-evolving manufacturing data base; and a Re-act framework commonality Evaluation agent that gives real-time, custom-made evaluation to empower engineers with insights for provider enchancment. These enhancements considerably elevate audit effectivity and effectiveness, with testing eventualities demonstrating an enchancment of over 24%.