
Cohere
Cohere · Coding · Other
Cohere is an enterprise AI company that builds the Command model family and the North agent platform, with a focus on private deployment and data control.

About Cohere
What Is Cohere
Cohere is an AI company founded in 2019 by Aidan Gomez, Ivan Zhang, and Nick Frosst. Gomez is one of the authors of the Transformer paper, the 2017 research that set the direction for modern language models. The company sells to businesses rather than consumers, and its whole pitch centers on one idea: your data and your models should stay under your control.
The product line splits into two halves. The Command family handles text generation, translation, reasoning, and retrieval-augmented generation (RAG), which grounds answers in your own documents. North is the layer on top, a workspace where teams build agents, automations, and lightweight apps over company knowledge. Customers pick how much of Cohere they want to run themselves, from a hosted API down to a private install inside their own data center.
The tradeoff is scope. Cohere does not chase consumer chat apps or the biggest open-ended model catalog, so it is not the place to look for a general chatbot like ChatGPT. Its models lean toward accuracy on enterprise tasks and efficient hardware use. Command A runs on two GPUs, which keeps private deployment cheaper than models that need a large cluster. Teams that want a huge model zoo or the lowest possible per-token price on general tasks usually look elsewhere.
Getting Started
- Create an account at dashboard.cohere.com and generate an API key under the API Keys section.
- Install the SDK with pip install cohere or npm install cohere-ai, then set CO_API_KEY in your environment.
- Send a chat request to the command-a-03-2025 model and test it on a task you already care about.
- Add connectors or documents to try RAG, so the model answers from your own data rather than its training.
- Move to a cloud AI service, a private VPC, or an on-premises install when the pilot has to go to production.
Product Information
A quick look at Cohere's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Enterprise engineering teams
- Regulated businesses in finance and healthcare
- Developers who need multilingual text work
- Data teams building search and classification
Tasks
- Answering questions over internal documents
- Running multi-step agents
- Translating business content
- Reading charts and forms
- Classifying and clustering text
Scenarios
- A bank that cannot send customer records off-site
- A support team answering in twelve languages
- A research pilot that has to prove itself before rollout
- A company connecting AI to its own systems
Key features
Command Model Family
The Command line is Cohere's core text generation engine, and it now spans several focused models instead of one generalist. Command A is the workhorse at 111 billion parameters with a 256k context window, built for tool use, agents, and RAG. Around it sit Command A Reasoning for step-by-step problems, Command A Vision for images, Command A Translate for 23-language translation, and the smaller Command R7B for cheap, fast jobs.
North Agent Platform
North is where Cohere moves from raw models to a working product. Teams build reusable agents and automations from plain prompts, give them shared knowledge through libraries, and let them keep context across sessions with memory. A visual builder, prebuilt templates, and live monitoring turn an agent from a demo into something a department can run day to day.
Retrieval-Augmented Generation
RAG is the thread through most of Cohere's lineup. The model fetches relevant passages from your documents before it answers, which cuts down invented facts and lets replies carry citations. For enterprise work, that grounding is often the difference between a prototype nobody trusts and a tool people rely on.
Private and Air-Gapped Deployment
Cohere offers four ways to run its models: the hosted platform, cloud AI services like Bedrock and Azure, a private cloud VPC, and a fully on-premises install. The on-premises path includes air-gapped setups where machines never touch an outside network. For banks, hospitals, and governments, that option is often the reason Cohere gets the meeting at all.
Multilingual Coverage
Command A and Command A Translate both work across 23 languages, including English, Spanish, Portuguese, Japanese, Korean, Arabic, and Hindi. The models can reply in the user's language or switch output to another on request, and they handle cross-lingual work like answering a question about a document written in a different language.
Embed and Rerank
Embed turns text and images into vectors that power search, classification, and clustering, and Rerank sits in front of an existing search system to reorder results by relevance. Both are drop-in pieces. You keep the search stack you already run and add Cohere where the ranking quality is weakest.
Enterprise Controls in North Admin
North Admin gives IT teams the levers that large rollouts require. Admins set roles and permissions, decide which models each group can use, and watch token spend in real time. Guardrails filter content and validate responses, while autonomy policies keep agents inside the actions they are cleared to take. Deployments carry SOC 2 Type 2, ISO 27001, and ISO 42001 certifications.
Connectors and Integrations
North connects to the tools a business already runs, including Slack, SharePoint, OneDrive, Microsoft Outlook and Exchange, Jira, Linear, Notion, and GitHub, with financial data providers such as PitchBook, Crunchbase, and S&P Global on the way. Connectors let agents read and act inside those systems instead of forcing a team to copy data into a new silo.
Pros and cons
Pros
- Private and air-gapped deployment lets regulated teams keep data on their own hardware.
- Command A runs on two GPUs, which lowers the cost of on-premises inference.
- Multilingual models cover 23 languages so one stack serves global markets.
- North ships with connectors, guardrails, and admin controls instead of leaving you to build them.
- The hosted API, free trial, and cloud marketplaces make it easy to test before buying hardware.
Cons
- There is no flagship consumer app, so it does not fit someone who wants a ChatGPT-style assistant.
- The model catalog is narrower than what major cloud providers offer, so niche models come from elsewhere.
- Production rollouts, private deployment, and enterprise pricing run through a sales conversation rather than a public self-serve page.
- Fine-grained features like North Admin, autonomy policies, and air-gapped installs are aimed at organizations, not individuals.
Frequently asked questions
Cohere is an enterprise AI company that builds large language models and the North agent platform. Its focus is helping businesses run AI on their own terms, including private and on-premises deployment, rather than selling a consumer chatbot.
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