Vector Similarity measures how closely two vector embeddings are related in meaning using mathematical distance or similarity metrics such as cosine similarity.
Voice AI platforms calculate Vector Similarity to improve semantic search, intent matching, recommendation systems, document retrieval, and conversation memory within RAG pipelines.