What is Cohere?

Learn about Cohere AI, the enterprise-focused company providing language models and RAG solutions for business applications and internal AI tools.

An enterprise AI company specializing in language models and embeddings for businesses building internal AI applications and search systems.

Cohere provides large language models, embedding APIs, and retrieval-augmented generation tools designed specifically for enterprise deployment. Unlike consumer-facing AI companies, Cohere focuses on helping businesses integrate AI into their existing workflows, data systems, and products - often running on private infrastructure rather than public APIs.

Deep Dive

Cohere occupies a distinct position in the AI landscape: the enterprise-first alternative to OpenAI and Anthropic. Founded in 2019 by former Google Brain researchers including Aidan Gomez (a co-author of the original Transformer paper), the company has raised over $445 million and serves customers including Oracle, McKinsey, and Notion. The company's core offering centers on three capabilities. First, Command models for text generation and reasoning tasks. Second, Embed models that convert text into numerical vectors for semantic search and similarity matching. Third, Rerank models that improve search relevance by re-ordering results. This combination makes Cohere particularly strong for RAG implementations, where companies need to search their internal documents and generate responses grounded in that content. What distinguishes Cohere from competitors is deployment flexibility. Their models can run on major cloud platforms (AWS, Google Cloud, Azure), in private cloud environments, or even on-premises for organizations with strict data sovereignty requirements. This matters enormously for enterprises in regulated industries like finance, healthcare, and government. Cohere's embedding models deserve particular attention. The Embed v3 family consistently ranks among the top performers on retrieval benchmarks, supporting over 100 languages. For companies building semantic search, recommendation systems, or knowledge bases, these embeddings directly impact how well AI systems understand and retrieve relevant information. The enterprise focus extends to pricing and support. Rather than pay-per-token consumer pricing, Cohere offers annual contracts with committed capacity, dedicated support, and custom fine-tuning. This makes total cost of ownership more predictable for large-scale deployments. For marketers and content strategists, Cohere matters less as a consumer-facing AI (it powers few public applications directly) and more as infrastructure. When enterprises deploy internal AI search or customer service automation, Cohere is often the engine underneath. Understanding this helps explain why some AI-powered experiences feel different from ChatGPT - they may be running entirely different models optimized for different objectives.

Why It Matters

Cohere represents how AI is actually being deployed in large organizations - not as public chatbots but as infrastructure powering internal tools, search systems, and automated workflows. For marketers, understanding enterprise AI deployment helps explain why AI-powered experiences vary so dramatically. A company using Cohere-powered internal search may surface and cite content differently than one using OpenAI. As more businesses deploy private AI systems, the diversity of underlying models matters. Your content might perform excellently in ChatGPT but poorly in enterprise systems using different embeddings. The AI ecosystem is fragmenting, and Cohere is a major fragment.

Key Takeaways

Enterprise-first: deployment flexibility over consumer features: Cohere prioritizes running on private infrastructure, supporting data sovereignty requirements, and integrating with enterprise systems rather than building consumer applications.

Embedding strength powers enterprise search applications: Cohere's Embed models consistently rank among the best for retrieval tasks, making them a go-to choice for companies building semantic search and RAG systems.

Co-founded by Transformer paper co-author: Aidan Gomez helped write the foundational 'Attention Is All You Need' paper that enabled modern LLMs, lending technical credibility to Cohere's approach.

Powers AI infrastructure, not consumer applications: You likely won't interact with Cohere directly, but it may power the enterprise AI tools and search systems you use at work.