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Agentic GraphRAG: AI’s Logical Edge — Stephen Chin, Neo4j
Agentic GraphRAG: Multi-Agent Knowledge Graph
GraphRAG vs. Traditional RAG: Higher Accuracy & Insight with LLM
How To Do Context Engineering (RAG, Agentic Search, Graph)
Background of Agentic Graph Rag

AI models are getting tasked to do increasingly complex and industry specific tasks where different retrieval approaches provide ... Speaker: Akhil Hemanth Resources: Get Started with Aura - Deployment Center - Want to learn more about Want to learn more about Generative AI + Machine Learning? Read the ebook here ... If you want to know how to do context engineering the way real production AI systems actually do it — not the prompt-engineering ... Learn more about GraphRAG here → Context is the biggest bottleneck in getting AI to do what you want. Want to learn more about AI agents and assistants? Register for Virtual Agents Day here → Download the ...
This in-depth session from the AI Agents Conference 2025 explores how Sign up to get my learning resources: In this advanced (301-level) session, we go beyond ... Your AI agent shouldn't need a decision tree to decide how to investigate. The answers to complex questions often don't live in a ... Code along with us! Click on the links below:* * Codelab link → Retrieval Augmented Generation is THE way to give your AI agents the ability to search and leverage your documents and ... For more information about Stanford's Artificial Intelligence professional and graduate programs, visit:
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For 2026, Agentic Graph Rag remains one of the most talked-about profiles.
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Last Updated: June 11, 2026
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