Retrieval-Augmented Generation (RAG) changed how we build AI apps, but its reliance on flat vector similarity often misses the deep relationships within data. Enter Knowledge Fabrics.
From Vectors to Relationships
By mapping your data into a Knowledge Graph before querying, you provide the AI with a structural understanding of how entities relate to one another. This "GraphRAG" approach allows for much more complex reasoning, such as "How did this specific reorg impact our delivery velocity in the APAC region?"
Knowledge Fabrics provide:
- Structural Context: Understanding hierarchy and causality.
- High Precision: Drastically reduced hallucinations in specialized domains.
- Explainability: The ability to trace a response back to specific nodes in the graph.