{"componentChunkName":"component---src-templates-tag-js","path":"/pensieve/tags/rag/","result":{"data":{"allMarkdownRemark":{"totalCount":2,"edges":[{"node":{"frontmatter":{"title":"GraphRAG in Production — Hybrid Retrieval That Auditors Can Trust","description":"How Neo4j knowledge graphs plus vector and full-text retrieval produce explainable answers for financial due diligence — patterns from building a GraphRAG knowledge engine.","date":"2026-03-01","slug":"/pensieve/graphrag-production","tags":["GraphRAG","Neo4j","RAG","LLM","Production"]}}},{"node":{"frontmatter":{"title":"Sadeeq Al-Siha Medical Chatbot","description":"Medical RAG QA with Meditron 7B, Qdrant, and PubMedBERT for evidence-grounded clinical answers","date":"2024-01-15","slug":"/projects/sadeeq-al-siha","tags":["LLM","Chatbot","Healthcare","RAG"]}}}]}},"pageContext":{"tag":"RAG"}},"staticQueryHashes":["1064330971","1994492073","2009693873","3298314076"]}