Introduction Vector search indexing pipelines are the backbone of modern AI systems that rely on semantic understanding instead of keyword matching. In simple terms, these tools take unstructured data—text, images, audio, or code—and convert it into high-dimensional vector embeddings that can be efficiently searched for similarity. This enables applications like retrieval-augmented generation, semantic search, recommendation Read More