How Data Graphs Built a True Hybrid Graph RAG Platform

Data Graphs, a UK-based platform company, has developed a hybrid graph retrieval-augmented generation (RAG) platform that integrates a proprietary graph database, full-text search, vector embeddings, workflow automation, and an Agentic AI layer. This platform is designed to handle complex, highly connected data across various industries, serving as both a system of record and a context layer. The company emphasizes the limitations of vector-only retrieval methods, advocating for a combination of structured data retrieval with semantic similarity retrieval from unstructured content, allowing an AI agent to dynamically select the best retrieval path. They chose Qdrant for its hybrid cloud deployment, payload filtering, and infrastructure automation capabilities, which seamlessly integrate with their existing systems. The resulting architecture enables blended retrieval and reasoning, utilizing both structured graph queries and vector retrieval to deliver accurate and domain-aware AI responses. As Data Graphs moves towards a machine-first future, the integration of these technologies demonstrates the potential for achieving true hybrid intelligence, offering a sophisticated context layer for AI applications.