How do you design scalable vector retrieval systems for LLMs?

Scalable vector retrieval systems use distributed indexing, ANN algorithms, and embedding optimization for efficient semantic search.

RAG systems rely heavily on vector retrieval infrastructure. As datasets grow to billions of embeddings, exact nearest-neighbor search becomes computationally infeasible.

Scalable systems therefore use:

Popular ANN algorithms include:

The architecture balances recall quality, latency, and infrastructure cost.