Vector databases form the indexing backbone of modern Generative AI and RAG architectures. In this guide, we compare the 4 leading options to help you choose the best fit for your workload. 1. Pinecone: The Fully-Managed Serverless Leader Pinecone’s serverless architecture separates compute from storage, drastically reducing costs for intermittent workloads while offering zero-maintenance scaling. […]
Building a demo RAG script in a Jupyter notebook takes 10 minutes, but scaling a production Retrieval-Augmented Generation (RAG) pipeline to handle millions of documents with sub-second latency and zero hallucinations requires rigorous engineering. Key Steps in Production RAG Architecture Document Ingestion & Semantic Chunking: Splitting documents based on semantic boundaries rather than arbitrary character […]
