Modern organizations frequently rely on chat-based platforms (e.g., Slack, Microsoft Teams, and Discord) for day-to-day communication and decision-making. As conversations evolve, organizational knowledge can get buried, prompting repeated searches and discussions. While maintaining shared documents, such as Wiki articles for the organization, offers a partial solution, it requires manual and timely efforts to keep it up to date, and it may not effectively preserve the social and contextual aspect of prior discussions. Moreover, reaching a consensus on document updates with relevant stakeholders can be time-consuming and complex. To address these challenges, we introduce CHOIR (Chat-based Helper for Organizational Intelligence Repository), a chatbot that integrates seamlessly with chat platforms. CHOIR automatically identifies and proposes edits to related documents, initiates discussions with relevant team members, and preserves contextual revision histories. By embedding knowledge management directly into chat environments and leveraging LLMs, CHOIR simplifies manual updates and supports consensus-driven editing based on maintained context with revision histories. We plan to design, deploy, and evaluate CHOIR in the context of maintaining an organizational memory for a research lab. We describe the chatbot's motivation, design, and early implementation to show how CHOIR streamlines collaborative document management.

翻译：现代组织经常依赖基于聊天的平台（如Slack、Microsoft Teams和Discord）进行日常沟通与决策。随着对话的演进，组织知识可能被埋没，导致重复搜索和讨论。虽然维护共享文档（如组织的Wiki文章）提供了部分解决方案，但这需要人工及时更新，且可能无法有效保留先前讨论的社会与情境背景。此外，与相关利益方就文档更新达成共识往往耗时且复杂。为应对这些挑战，我们提出了CHOIR（基于聊天的组织智能存储库助手），这是一种能够与聊天平台无缝集成的聊天机器人。CHOIR能自动识别并提议相关文档的编辑，发起与相关团队成员的讨论，并保留情境化的修订历史。通过将知识管理直接嵌入聊天环境并利用大型语言模型，CHOIR简化了人工更新流程，并支持基于带修订历史的维护情境进行共识驱动的编辑。我们计划在研究实验室维护组织记忆的背景下设计、部署和评估CHOIR。本文阐述了该聊天机器人的设计动机、架构与早期实现，以展示CHOIR如何优化协作式文档管理。