Agents will continue to be an important part of enterprise AI adoption, Cohere told BetaKit

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Enterprise retrieval augmented generation (RAG) remains integral to the current agentic AI craze. Taking advantage of the continued interest in agents, Cohere released the latest version of its embeddings model with longer context windows and more multimodality. Cohere’s Embed 4 builds on the multimodal updates of Embed 3 and adds more capabilities around unstructured data. Thanks to a 128,000 token context window, organizations can generate embeddings for documents with around 200 pages. “Existing embedding models fail to natively understand complex multimodal business materials,‬‭ leading companies to develop cumbersome data pre-processing pipelines that only slightly‬‭ improve accuracy,” Cohere said in a blog post. “Embed 4 solves this problem, allowing enterprises and their employees to‬‭ efficiently surface insights that are hidden within mountains of unsearchable information.‬”Enterprises can deploy Embed 4 on virtual private clouds or on-premise technology stacks for added data security. Companies can generate embeddings to transform their documents or other data into numerical representations for RAG use cases

Ottawa is investing $240 million in Cohere's $725 million project to acquire AI compute resources at a new Canadian data center set to open this year.