发表机构
GPT Lab; Faculty of Information Technology and Communication Sciences; Tampere University; DIMECC Oy; University of Oulu（GPT实验室; 信息技术与传播科学学院; 坦佩雷大学; DIMECC公司; 奥卢大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究设计实现了一种具备治理感知能力的多租户AI沙箱，满足工业界与学术界协作式AI实验的需求，为相关平台的部署扩展提供了实用经验。
AI 中文摘要
工业界与学术界的协作式AI实验需要能支持快速原型开发，同时保持受控访问、租户隔离和透明工作流的平台。尽管人们对AI沙箱的兴趣日益增长，但关于如何设计和实现将实验能力与治理要求相结合的平台的实用指南仍然有限。本研究提出了一种面向结构化实验、可在项目和利益相关者群体间生成可复用评估证据的、具备治理感知能力的多租户AI沙箱的设计与实现方案。该沙箱是在工业界与学术界合作中，基于与工业伙伴迭代完善的需求开发而成的。其参考架构将多租户用户界面与后端控制平面分离，将执行和数据管理功能置于专用层。该平台支持受管控的用户入职、以项目为中心的协作、对AI服务的托管访问、审批工作流、审计日志记录以及可追踪的实验。实验配置、上下文信息和治理决策被存储为持久记录，使得证据和结果可在项目间进行比较和复用。开发过程为在协作研究和工业环境中部署与扩展具备治理感知能力的AI沙箱平台提供了实用经验。
英文摘要
Collaborative AI experimentation across industry and academia requires platforms that enable rapid prototyping while preserving controlled access, tenant separation, and transparent workflows. Despite growing interest in AI sandboxes, there is still limited practical guidance on how to design and implement platforms that integrate experimentation capabilities with governance requirements. This work presents the design and implementation of a governance-aware, multi-tenant AI sandbox for structured experimentation and the generation of reusable evaluation evidence across projects and stakeholder groups. The sandbox was developed within an industry-academia collaboration based on requirements that were iteratively refined with industrial partners. Its reference architecture separates the multi-tenant user interface from the backend control plane and places execution and data-management functions in dedicated layers. The platform supports governed user onboarding, project-centered collaboration, managed access to AI services, approval workflows, audit logging, and traceable experimentation. Experiment configurations, contextual information, and governance decisions are stored as persistent records, allowing evidence and outcomes to be compared and reused across projects. The development process provides practical lessons for deploying and extending governance-aware AI sandbox platforms in collaborative research and industrial environments.
