GraphRAG (Graph Retrieval-Augmented Generation) combines knowledge graph relationships with vector search to provide AI systems with both semantic context and factual accuracy. Unlike pure vector search which only finds similar content, GraphRAG understands entity relationships, hierarchies, and validated connections in your knowledge graph. VISEON enables GraphRAG by ensuring your Schema.org entities are properly connected with accurate @id references, creating a queryable graph structure. We support hybrid Vector/RAG solutions via Model Context Protocol (MCP), allowing AI agents to traverse your knowledge graph and retrieve precise, contextual information for agentic commerce workflows.
