RAG10 min read
Hybrid Retrieval for RAG — Combining Dense and Sparse Search
Explore why dense embeddings alone fail, and how hybrid search combining vector similarity with BM25 sparse retrieval dramatically improves RAG quality.
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RAG10 min read
GraphRAG — Combining Knowledge Graphs With Vector Search
Build GraphRAG systems using knowledge graph traversal and vector search together to handle complex multi-hop questions and relationship-aware context retrieval.
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RAG6 min read
Long Context vs RAG — When to Stuff the Context and When to Retrieve
Choose between long-context LLMs and RAG by understanding the lost-in-the-middle problem, cost dynamics, and latency tradeoffs.
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RAG6 min read
RAG Metadata Filtering — Using Structured Data to Sharpen Retrieval
Master metadata filtering in RAG systems: design schemas, implement self-querying, combine filters with vector similarity, and isolate tenants securely.
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RAG10 min read
Multimodal RAG — Searching Images, Tables, and PDFs Together
Build RAG systems that handle PDFs, tables, images, and charts by combining text extraction, table embeddings, and vision encoders for unified multimodal search.
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