You’ve got 100 GB of PDFs, notes, and exported chat logs you’d love to query with natural language. So you reach for the standard RAG playbook: chunk everything, embed it, store the vectors in FAISS or a hosted vector DB. Then you check the index size and it’s 150–700 GB — larger than the data […]