Deployment

Enterprise Knowledge Structuring

Why Your Documentation Is Broken for AI — and the Restructuring Patterns That Fix It

作者

Tenten AI FDE Team

Forward Deployed Engineering

发布日期

2026年1月10日

阅读时间

16 min

knowledge managementRAGdocumentationchunkingsemantic search
Enterprise Knowledge Structuring

摘要

Enterprise documentation is not written for AI retrieval. It is written for human navigation, organizational compliance, and historical record-keeping. The structure optimized for human use — nested folder hierarchies, version-controlled PDFs, SharePoint wikis with inconsistent tagging — is pathologically bad for machine retrieval.

The result: organizations build RAG systems on top of their existing documentation without restructuring it, encounter poor retrieval quality, and conclude that RAG does not work well for their use case. The real conclusion is that RAG works fine; their documentation is structured in ways that make high-quality retrieval impossible.

This whitepaper describes the documentation restructuring patterns Tenten AI has implemented to make enterprise knowledge bases retrievable. The patterns are practical: they do not require replacing existing documentation systems, and they do not require manual re-writing of existing documents. They require restructuring how documents are ingested, indexed, and accessed.

完整内容

解锁完整白皮书

提交您的信息后可立即解锁完整内容。我们每月发送一至两封技术通讯,随时可取消订阅。

提交即代表您同意接收 Tenten AI 的技术资讯,可随时退订。

AI原生产品
新时代已来

数周内交付您的第一个AI应用场景,而非数季度。