Source: https://pageindex.ai/blog/ocr Vector RAG: Why It’s Winning in Production In a...
Source: https://pageindex.ai/blog/ocr
Vector RAG: Why It’s Winning in Production
In a world where LLMs are the new CPUs, the bottleneck isn’t the model – it’s the data.
Vector RAG (Retrieval‑Augmented Generation) moves the needle by turning document retrieval into a fast, scalable, and cost‑effective operation.
1. Quick Recap: Classic RAG vs. Vector RAG
RAG retrieval strategies without a vector database: BM25, keyword indices, knowledge-in-bundle — and when embeddings earn their…
Vector RAG is the reflexive answer to "give the model more context," and when I built a production...
An architecture-focused comparison of Graph RAG and vector RAG: chunking, storage, retrieval behavior, trade-offs, and hybrid…
The first two parts of this series covered why production RAG systems fail and how the quality of the...
A practical look at the retrieval layer of RAG — what a vector database actually does, why keyword...
A practical RAG database design guide covering SQL, BM25, vector search, reranking, security, cost, and locality-aware context…
