Cohere Unveils Embed 4 for Multimodal Enterprise Search

Cohere Unveils Embed 4 for Multimodal Enterprise Search

Image: Cohere
Cohere has launched Embed 4, a state-of-the-art multimodal embedding model designed to enhance enterprise search capabilities across various industries.

Cohere has introduced Embed 4, a cutting-edge multimodal embedding model aimed at improving enterprise search and retrieval capabilities. Announced on their website, Embed 4 is designed to handle complex multimodal documents, such as PDFs and presentations, by accurately searching and retrieving data across text, images, tables, and more.

The model supports over 100 languages, including Arabic, Japanese, Korean, and French, making it suitable for global enterprises. It is particularly optimized for industries with stringent security requirements, such as finance, healthcare, and manufacturing, allowing deployment in virtual private cloud and on-premise environments.

Embed 4 also offers a breakthrough context length, capable of generating embeddings for documents up to 128K tokens, equivalent to around 200 pages. This feature is crucial for handling extensive documents like financial reports and legal contracts. Additionally, the model's efficiency in data storage can save organizations up to 83% on storage costs.

Available on Cohere's platform, Microsoft Azure AI Foundry, and Amazon SageMaker, Embed 4 is set to power the next generation of AI applications, enhancing productivity and efficiency across various sectors.

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