Vector Databases: Semantic Search at Scale

From keyword matching to finding meaning. The database that understands context.

Vector databases are the infrastructure that makes AI search work at scale. Instead of matching keywords, they find semantically similar results by querying embeddings in high-dimensional space. This bundle explains how embeddings translate meaning into mathematics, how cosine similarity measures closeness, and why every modern AI system needs a vector database to power semantic search.