An Embedding Model converts text, audio, or other content into vector representations that preserve semantic relationships. These vectors enable similarity search, retrieval, clustering, and recommendation tasks.
Voice AI platforms generate embeddings from transcripts, documents, and customer conversations before storing them in vector databases. Embedding Models enable accurate retrieval during AI-powered voice interactions.