What are embeddings used for?

Embeddings convert text, images, or other data into dense vectors that capture semantic meaning. They power semantic search, recommendation, classification, clustering, and retrieval-augmented generation.

VePrompts

Collections

Embedding Guides

Learn how to choose, evaluate, and deploy embedding models for search, RAG, and classification.

How to Choose an Embedding Model

Compare OpenAI, Cohere, Voyage, Jina, and open-source embeddings by task and budget.

Embeddings for RAG vs Classification

Match embedding models to retrieval, classification, clustering, and semantic search.

Multilingual Embeddings

Build cross-lingual semantic search and RAG for global products.