4 articles found
How BlueRobin combines multi-model vector search, Reciprocal Rank Fusion, knowledge graph traversal, and full-document context assembly to answer complex questions across your entire archive.
How BlueRobin extracts named entities from every document, resolves them into a canonical taxonomy, and stores a property graph that connects people, organisations, dates, and events across your entire archive.
A production blueprint for combining graph traversal and vector search to improve recall and precision in document retrieval.
Model and query entity relationships using FalkorDB (Redis Graph) for knowledge graphs and connected data in .NET applications.