LawDigitalTwin: A Proactive and Emotionally Aware Digital Agent for Complex Commercial Disputes

Zhengzhen Qian, Xiaoliang Luo, Huaxiuyue Wang, Yilei Zhu

Keywords: Legal AI, Large Language Model, AI Agent, Multi Modal, Emotionally-Aware AI, Law Application

Paper Type: Demo papers

Abstract: The resolution of modern commercial disputes, particularly those involving intertwined issues like supply chains and financial factoring, poses significant challenges due to their complexity and tight coupling with business operations. We introduce LawDigitalTwin, a proactive and emotionally aware digital agent designed to navigate the entire lifecycle of complex commercial disputes. Unlike traditional legal solutions that focus solely on question-and-answer interactions, our system leverages Large Language Models (LLMs) to integrate a structured legal workflow, offering end-to-end support that encompasses evidence gathering, legal fact summarization, lawyer pairing, and strategic litigation planning. A key innovation of LawDigitalTwin is its ability to dynamically integrate emotional recognition into formal legal reasoning processes, which significantly enhances user trust and engagement. Through a case study of a multi-party dispute regarding a smart device supply chain contract, we demonstrate LawDigitalTwin’s capability in deconstructing complexities, formulating effective strategies, and executing essential actions such as asset preservation. This demonstration underscores the potential of AI to transform and democratize access to high-stakes legal services.

Submission Number: 44