11 posts about knowledge graphs by 9 contributors.
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In our POC, the Graph RAG agent successfully identified a hidden supply chain risk that the traditional model missed, resulting in a significant score adjustment and a "Superior" verdict. This demonstrates that Graph RAG is not just a technological upgrade, but a risk-mitigation tool that provides tangible, measurable value to enterprise lending portfolios.
By leveraging LangGraph, we created a system where the Graph Traversal Agent maps the structural landscape, the RAG Agent provides the regulatory and historical context, and the Synthesis Agent delivers a decision that is both mathematically grounded in graph theory and explainable through natural language. This architecture ensures that enterprises can detect sophisticated synthetic identity fraud rings that would otherwise slip through the cracks of flat, tabular data pipelines.
Our Multi-Agent LangGraph POC demonstrates how specialized agents can handle the complexity of chunking, graph construction, and contextual retrieval, resulting in highly accurate and explainable AML investigations. This approach transforms raw, fragmented data into a coherent web of financial intelligence.
Unlock enterprise AI potential with semantic data modeling. Enhance search, integration, and AI accuracy by organizing data by meaning, not just structure.
Unlock enterprise AI with GraphRAG, Azure AI Search, and .NET. Enhance LLMs with knowledge graphs for deeper context and reasoning.
Explore advanced AI retrieval pipelines beyond RAG: multi-stage, hybrid search, query transformation, knowledge graphs, and agentic workflows.
Unlock AI potential with knowledge graphs for .NET developers. Master relationships, context, and reasoning for smarter applications.
Unlock Agentic RAG with Knowledge Graphs! Learn how Neo4j enhances AI agents at the 2025 AI Agents Conference. Boost your RAG with graph power!
Join industry leaders, researchers, and innovators as we explore the cutting-edge of AI agent technology. Discover the future of autonomous systems and intelligent automation. How to build AI Agents, workflow using AI Agents, Agentic AI, future of AI Agents, AI Hallucinations, Agentic RAGs with…
AI hallucinations are a major hurdle for enterprise adoption. This article explores the root causes, from statistical guesswork to data limitations, and presents seven practical solutions. Learn how Retrieval-Augmented Generation (RAG), knowledge graphs, structured prompting, and human oversight can mitigate risks and build trustworthy AI systems.
Discover how emerging AI technologies are reshaping industries, boosting efficiency, and driving innovation. Explore real-world applications, benefits, and challenges to understand the true impact of AI in today’s world.
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