LLM Engineering8 min read
FAISS vector stores in production RAG
How to use FAISS for production RAG. Index types, persistence, memory trade-offs, and the 4 settings that decide if FAISS beats a managed vector DB.
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Embeddings
Explore our latest articles and insights about Embeddings.
Explore posts
6 posts in total
LLM Engineering11 min read
Choosing an embedding model for RAG
How to pick an embedding model for production RAG. The 5 criteria that matter, the benchmarks that lie, and the migration cost nobody warns you about.
LLM Engineering11 min read
RecursiveCharacterTextSplitter: a deep dive for RAG
How RecursiveCharacterTextSplitter works, why it beats naive chunking, and the separator order that makes or breaks retrieval quality.
AI Engineering in Practice10 min read
The 'brain' of RAG: a guide to embeddings & vector databases
Understand how embeddings and vector databases work under the hood. Learn how computers translate text meaning into numbers and search millions of docum...
AI Engineering8 min read
Vector databases and embeddings: the brain of RAG
Learn how embeddings and vector databases power RAG systems. Understand semantic search, cosine similarity, metadata filtering, and choose between open-...
AI Engineering9 min read
Retrieval-augmented generation (RAG): giving LLMs an open book
How retrieval works in production. Learn how RAG solves LLM limitations by connecting models to external documents. Master chunking, embeddings, vector dat