Building a Vector Search System End-to-End - Part I

Vector search powers modern AI retrieval systems, but its mechanics often feel like magic. This article breaks the process down step by step—extracting text from PDFs, chunking documents, generating embeddings, and indexing them with FAISS. By also implementing brute-force similarity search from scratch, the author reveals how vector databases trade accuracy, speed, and memory to make semantic search scalable.