The Excellence
Directory Platform Template

Commercial text embedding model from Cohere with multilingual support and 1,024-dimensional vectors. Optimized for semantic search and retrieval tasks. This is a commercial API service with pay-per-use pricing.

Open-source PostgreSQL extension and Python library that automates embedding generation and synchronization for RAG and semantic search applications. Features pgai Vectorizer for declarative embedding pipelines. This is an OSS solution.

Commercial embedding models built for enterprise-grade semantic search and RAG applications. Features voyage-3 and voyage-3-large models with multimodal support. This is a commercial API service with usage-based pricing.

Module of Google’s Machine Learning Crash Course that explains word and text embeddings, how they are obtained, and the difference between static and contextual embeddings, giving essential background for using vector representations in vector databases and similarity search systems.

Puck is an open-source vector search engine designed for fast similarity search and retrieval of embedding vectors.