对比主流企业AI助手的零数据留存实现方案，揭示其架构与合规权衡。
Zero Data Retention in LLM-based Enterprise AI Assistants: A Comparative Study of Market Leading Agentic AI Products
- 通过分析Salesforce和Microsoft的AI助手架构，对比零数据留存设计。
- 发现大模型服务商如OpenAI、Anthropic支持零留存，但企业应用需额外保障。
- 适合关注企业AI隐私与合规的开发者及决策者参考。
企业AI助手在提升生产力的同时，面临数据治理、合规及商业隐私挑战，尤其在医疗与金融领域更为关键。随着大型语言模型（LLM）企业助手在企业中的广泛应用，实现零数据留存已成为当务之急。本文研究了主流企业级大模型应用中零数据留存政策的实施路径，重点分析了行业两大巨头——Salesforce与Microsoft的技术架构差异。Salesforce AgentForce与Microsoft Copilot作为领先的企业级AI助手，在客户服务等领域显著提升效率。研究揭示了从应用层到大模型服务提供商（如OpenAI、Anthropic、Meta）在零数据留存策略上的系统性权衡，涵盖架构设计、合规要求与可用性之间的取舍，为构建可信企业级AI系统提供实践依据。
原文摘要 · Abstract (English)
Governance of data, compliance, and business privacy matters, particularly for healthcare and finance businesses. Since the recent emergence of AI enterprise AI assistants enhancing business productivity, safeguarding private data and compliance is now a priority. With the implementation of AI assistants across the enterprise, the zero data retention can be achieved by implementing zero data retention policies by Large Language Model businesses like Open AI and Anthropic and Meta. In this work, we explore zero data retention policies for the Enterprise apps of large language models (LLMs). Our key contribution is defining the architectural, compliance, and usability trade-offs of such systems in parallel. In this research work, we examine the development of commercial AI assistants with two industry leaders and market titans in this arena - Salesforce and Microsoft. Both of these companies used distinct technical architecture to support zero data retention policies. Salesforce AgentForce and Microsoft Copilot are among the leading AI assistants providing much-needed push to business productivity in customer care. The purpose of this paper is to analyze the technical architecture and deployment of zero data retention policy by consuming applications as well as big language models service providers like Open Ai, Anthropic, and Meta.
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