Integrations

Use Cohere's models with the tools you love.

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Qdrant is an open-source vector similarity search engine and vector database. It provides a production-ready service with a convenient API to store, search, and manage points - vectors with an additional payload. Qdrant is tailored to extended filtering support. It makes it useful for all sorts of neural-network or semantic-based matching, faceted search, and other applications.

Qdrant is written in Rust, which makes it fast and reliable even under high load.


Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering.

The text2vec-cohere module allows you to use Cohere embeddings directly in the Weaviate vector search engine as a vectorization module.


The Pinecone vector database makes it easy to build high-performance vector search applications. Use Cohere to generate language embeddings, then store them in Pinecone and use them for Semantic Search.


Cohere offers optimized containers that enable low latency inference on a diverse set of hardware accelerators available on AWS, providing different cost and performance points for Sagemaker customers.


Integrate the Surge AI labeling platform into your Cohere workflow.


Use Scale's labelled datasets with Cohere's Large Language Models.