Cohere built its platform specifically for enterprise use cases with a focus on RAG (retrieval-augmented generation), multilingual support, and deployment flexibility. Their Command models are competitive generalists, but their real differentiation is in their Embed and Rerank models which are widely considered the best-in-class for retrieval pipelines.
Cohere offers three main endpoints: Generate (for Command models), Embed (for converting text to vectors), and Rerank (for scoring and reordering search results). The Rerank model is particularly powerful — you retrieve candidate documents via cheap vector search, then use Rerank to score the top-k with a smaller, specialized model that significantly improves retrieval quality. All endpoints support private deployment via AWS, GCP, Azure, and on-prem.
Command-R+: $3 input / $15 output per M tokens. Command-R: $0.50/$1.50. Embed v3: $0.10 per M tokens. Rerank v3: $1 per 1000 searches. Enterprise dedicated deployments priced separately.
Oracle, Notion, LivePerson, Fujitsu, and many Fortune 500 enterprises for search and RAG. Less popular for general chat but dominant in enterprise retrieval.