Legal contracts in the custody and fund services domain govern critical aspects such as key provider responsibilities, fee schedules, and indemnification rights. However, it is challenging for an off-the-shelf Large Language Model (LLM) to ingest these contracts due to the lengthy unstructured streams of text, limited LLM context windows, and complex legal jargon. To address these challenges, we introduce LAW (Legal Agentic Workflows for Custody and Fund Services Contracts). LAW features a modular design that responds to user queries by orchestrating a suite of domain-specific tools and text agents. Our experiments demonstrate that LAW, by integrating multiple specialized agents and tools, significantly outperforms the baseline. LAW excels particularly in complex tasks such as calculating a contract's termination date, surpassing the baseline by 92.9% points. Furthermore, LAW offers a cost-effective alternative to traditional fine-tuned legal LLMs by leveraging reusable, domain-specific tools.

翻译：托管与基金服务领域的法律合约规范着关键条款，如核心服务商责任、费用结构及赔偿权利等。然而，由于此类合约文本通常呈现为冗长的非结构化数据流，且受限于大语言模型的上下文窗口长度及复杂的法律专业术语，现有通用大语言模型难以有效处理此类合约。为应对这些挑战，本文提出LAW（面向托管与基金服务合约的法律智能体工作流）。该框架采用模块化设计，通过协调领域专用工具与文本智能体来响应用户查询。实验表明，LAW通过集成多个专业智能体与工具，其性能显著超越基线模型。尤其在计算合约终止日期等复杂任务中，LAW以92.9个百分点的优势大幅领先基线模型。此外，通过复用领域专用工具，LAW为传统微调法律大语言模型提供了更具成本效益的替代方案。