Many organizations are experimenting with simple ways to use AI on top of their existing document repositories. A common approach is to connect a large language model directly to a SharePoint corpus using basic search or retrieval augmented generation. While this can appear attractive at first, it quickly runs into fundamental limitations.
Documents are not knowledge
SharePoint is designed to store documents, not to represent knowledge. Documents contain information, but the meaning, relationships and assumptions are implicit and scattered across files, versions and formats. When an LLM is connected directly to a document corpus, it can only retrieve fragments of text. It has no understanding of how concepts relate to one another or which information takes precedence.
As a result, answers often look plausible but are incomplete, inconsistent or misleading.
Similarity search does not scale
Most SharePoint plus LLM approaches rely on similarity search over document chunks. This works for simple questions, but as the volume and diversity of content grows, retrieval quality degrades. Important context is missed, exceptions are overlooked and subtle differences in terminology cause failures.
Chunking further amplifies the problem by breaking logical connections between related ideas. The LLM is then forced to guess how the pieces fit together.
No shared understanding of language
Organizations rarely use language in a clean, consistent way. Acronyms, aliases and internal terms evolve over time and often differ from standard industry usage. A document based approach has no durable way to capture these meanings. If a synonym is not explicitly written in the text, the system simply does not know it exists.
KnowledgeWay solves this by making terminology explicit in the Enterprise Knowledge Graph, so different words used by different teams still map to the same underlying concept.
Knowledge that improves over time
A SharePoint based solution does not learn. If an answer is wrong or incomplete, there is no systematic way to improve the underlying knowledge. The same mistakes are repeated again and again.
KnowledgeWay is designed to evolve. User feedback, expert input and agent driven curation continuously improve the quality of the knowledge graph and the answers built on top of it.
From documents to decisions
Connecting an LLM to SharePoint is a document search shortcut. KnowledgeWay is a knowledge platform. By transforming documents into a structured, curated Enterprise Knowledge Graph, KnowledgeWay delivers more reliable answers, better context and far greater long term value.
If you want AI that truly understands your organization, not just its file system, KnowledgeWay is the difference.