https://ai-blog.noorshomelab.dev/tags/neo4j/Recent content in Neo4j on AI VOIDHugoenFri, 20 Mar 2026 00:00:00 +0000https://ai-blog.noorshomelab.dev/rag-2-0-guide-2026/introduction-to-graphrag/Fri, 20 Mar 2026 00:00:00 +0000https://ai-blog.noorshomelab.dev/rag-2-0-guide-2026/introduction-to-graphrag/<h2 id="unlocking-relationships-introduction-to-graphrag-for-structured-knowledge-retrieval">Unlocking Relationships: Introduction to GraphRAG for Structured Knowledge Retrieval</h2> <p>Welcome back, fellow AI adventurer! In our journey through RAG 2.0, we&rsquo;ve explored how hybrid search and advanced embeddings can significantly boost retrieval accuracy. We&rsquo;ve seen how these techniques help us find <em>relevant chunks</em> of information. But what if your query isn&rsquo;t just about finding a chunk, but about understanding complex relationships between pieces of information scattered across many documents? What if you need to connect the dots across different concepts to answer a truly nuanced question?</p>https://ai-blog.noorshomelab.dev/rag-2-0-guide-2026/graphrag-n-hop-expansion-integration/Fri, 20 Mar 2026 00:00:00 +0000https://ai-blog.noorshomelab.dev/rag-2-0-guide-2026/graphrag-n-hop-expansion-integration/<h2 id="introduction-beyond-simple-chunks--the-power-of-graphrag">Introduction: Beyond Simple Chunks – The Power of GraphRAG</h2> <p>Welcome back, intrepid RAG explorers! In our previous chapters, we&rsquo;ve journeyed through the foundations of RAG, tackled advanced embeddings, and even explored the nuances of hybrid search. We&rsquo;ve seen how these techniques significantly improve context retrieval compared to basic chunking. However, even with powerful vector and keyword searches, standard RAG can still struggle with a particular class of questions: those requiring <strong>multi-hop reasoning</strong> or a deeper understanding of <strong>relationships</strong> between entities.</p>