Lettria, a knowledge graph vendor and AWS Partner, benchmarked graph-structured RAG against vector-only retrieval across four domain corpora and reported correctness improving from roughly 50% to abov…
FalkorDB's GraphRAG SDK is positioned as a key tool for network analysis applications in 2026, with ten production use cases including knowledge graph construction for RAG, fraud ring detection, and s…
FalkorDB released a community node for n8n that integrates GraphRAG, enabling AI agents to query a knowledge graph built from GitHub-hosted documentation. The node exposes five graph tools, allowing a…
FalkorDB has rewritten its core database engine in Rust, replacing the original C codebase with 80,000 lines of Rust, 357 merged pull requests, and passing 1,585 TCK scenarios and 1,322 flow tests. Th…
Grand View Research valued the global master data management (MDM) market at USD 19.9 billion in 2023 and projects it to reach USD 60.7 billion by 2030, a 17.4% CAGR, as enterprises adopt AI systems t…
FalkorDB CEO Guy Korland will demonstrate how to power agentic workflows with a knowledge graph for n8n and LangGraph/LangChain, addressing the fragmented data problem by combining documents, APIs, an…
A new guide from DPP Grid outlines the requirements for a supply chain database designed for AI and analytics workloads, emphasizing the need for a graph-based operational model that can trace events …
A production-ready chatbot requires grounded retrieval, conversational state, and an operational backbone, not just a model, according to a technical guide for developers. The guide recommends startin…
Python's graph ecosystem spans analysis and machine learning, with NetworkX as the default for prototyping and smaller jobs, while python-igraph, graph-tool, and NetworKit offer higher performance for…
Agentic workflows enable AI systems to plan, act, observe results, and revise next steps, moving beyond brittle scripts to handle variable, cross-system tasks. The UK government's AI Insights guidance…