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Graph RAG
33 posts about Graph RAG by 3 contributors.
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Articles about Graph RAG
- Article · AI Agents
Quantifying Graph RAG Impact on Credit Risk Assessment
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.
- Article · AI Agents
From Flat Features to Connected Insights: Graph RAG-Powered Credit Scoring vs. Traditional ML
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.
- Article · AI Agents
Advanced Chunking Strategies for Graph RAG in Transaction Narratives
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.
- Article · Langchain
Graph-Augmented Reasoning for Cash Management
Graph-augmented reasoning for cash management: combining graph traversal with LLMs for treasury intelligence and compliance.
- Article · Langchain
Graph-Native Fraud & Credit Risk for Cards
Leverage Graph-RAG Multi-Agent Systems for high-cardinality card fraud detection, enabling low-latency fraud ring identification.
- Article · Langchain
Enterprise Graph-RAG: Modeling Financial Risk Networks with Multi-Agent LangGraph
Enterprise Graph-RAG models financial risk networks with multi-agent LangGraph for real-time contagion and AML analysis.
