The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via ...
RAG retrieves documents but not decision logic, causing agents to act on expired rules. Decision context graphs encode ...
Latest Graphwise offering bridges the gap between complex enterprise data and functional AI agents, using ontologies reduces inaccurate answers 2X in benchmarks Equally important, the company ...
Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Graph Database technology for Entity-Event Knowledge Graph Solutions, is releasing AllegroGraph 8.2 with ...
Microsoft is making publicly available a new technology called GraphRAG, which enables chatbots and answer engines to connect the dots across an entire dataset, outperforming standard ...
Through natural language queries and graph-based RAG, TigerGraph CoPilot addresses the complex challenges of data analysis and the serious shortcomings of LLMs for business applications. Data has the ...
Memgraph, a leader in open-source, in-memory graph databases, is introducing a new capability designed to accelerate business adoption of graph-based retrieval-augmented generation (GraphRAG), Atomic ...
Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...
While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...
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