PDFs, websites, manuals, chats, emails and experience are inventoried and classified by trust and freshness.
ORQENIO PRACTICAL GUIDE
Building a Knowledge Hub: making company knowledge usable by people and AI
A Knowledge Hub is more than document storage. It connects sources, structure, searchability, approval status, freshness and permissions.
Topics, entities, products, processes and questions receive metadata and relationships so knowledge can be found and reused.
Semantic search and RAG can retrieve relevant information for an answer, but they do not replace source maintenance and permissions.
Unanswered questions and poor retrieval reveal knowledge gaps. Good systems use these signals to improve content deliberately.
RELATED QUESTIONS
Go deeper where needed.
How do you make company knowledge usable by AI?
Knowledge must be findable, current, structured and governed by clear access rights. Good knowledge systems separate sources, approval status and sensitive content while keeping answers traceable.
Open answer →Can PDFs be added to a knowledge base?
Yes. PDFs can be extracted, structured, categorized and enriched with metadata. The key questions are whether content is current and approved and whether tables, images or scanned pages need extra processing.
Open answer →What is semantic search?
Semantic search tries to understand the meaning of a query rather than matching exact words only. This helps users find relevant content even when wording differs from the source document.
Open answer →What are embeddings?
Embeddings are mathematical representations of text or other content. They make similarity machine-comparable and are often used for semantic search, recommendations and RAG systems.
Open answer →What does RAG mean in AI?
RAG stands for Retrieval-Augmented Generation. An AI system first retrieves relevant information from approved knowledge sources and then uses it as context for its answer.
Open answer →