An honest overview of Cohere AI for enterprise use in 2025

The world of AI is noisy, and with a new platform popping up every week, it’s easy to feel a bit lost. In the middle of all this noise, Cohere AI has staked its claim by focusing on one thing: building for businesses. It’s a seriously powerful platform, but let’s be clear, it’s definitely not for everyone.

This article is the straight scoop on what Cohere AI is, what it’s good at, and who it’s actually built for. We’ll break down their main products, how companies are using them, and what the pricing looks like. By the end, you’ll have a much better idea of whether it’s the right foundation for your company’s AI plans, especially if you don’t have a small army of AI developers on speed dial.

What is Cohere AI?

At its core, Cohere AI is a cloud-agnostic AI platform that gives businesses the building blocks, powerful large language models (LLMs) and other tools, to create their own AI applications. Think of it this way: while tools like ChatGPT are built for the general public, Cohere is laser-focused on what big companies need, like top-notch data privacy, security, and deployment options. You can run their models in the cloud or right on your own servers.

The platform is built around a few key model families. Their "Command" models are the writers, used for generating text. "Embed" models are the readers, built to understand the meaning behind words to power smarter search. And "Rerank" models are the librarians, organizing search results so the most relevant stuff is always at the top.

This focus on the enterprise makes perfect sense when you look at where Cohere came from. One of its founders, Aidan Gomez, was a co-author of the "Attention Is All You Need" paper. If you’ve been following AI, you know that’s the research that basically kicked off the entire modern generative AI boom. That kind of technical street cred is a big reason why large organizations trust them to help build custom AI apps.

The core products and features of Cohere AI

Cohere offers a potent toolkit for anyone looking to build an AI-powered application. The key thing to remember is that it’s a set of sophisticated building blocks, not a ready-made solution you can just plug in.

Cohere AI generative models: The Command family

The "Command" models, like Command R and the more powerful Command R+, are Cohere’s flagship text-generation LLMs. They’re tuned for business-specific tasks and can handle a bunch of different languages, which is a big deal for global companies.

One of their standout features is something called retrieval-augmented generation (RAG). It sounds complicated, but RAG is just a fancy way of saying the AI can use your own company documents to find answers. This ensures the information it gives is accurate and specific to your business. The catch? To make any of this work, you need a developer to hook into their API and build a whole application around it. It’s not a feature you can just flip a switch on.

Cohere AI retrieval and search models: Embed and Rerank

For RAG to do its job, the search has to be fantastic. That’s where "Embed" and "Rerank" come into play. The "Embed" model reads all your documents and turns them into numerical codes (called vectors) so a computer can grasp their meaning. When someone asks a question, the system finds the documents with the most similar meanings. Then, the "Rerank" model takes that list of possibilities and shuffles it to put the absolute best answers right at the top.

This combo is amazing for building things like an internal search engine for your company wiki or a customer support bot that can find the exact right paragraph in a giant help center. But again, you have to build it yourself. If that sounds like a massive project, you’re right. It is. For teams who want to connect all their knowledge without the heavy engineering lift, platforms like eesel AI link up to all your sources like Google Docs, Confluence, and old Zendesk tickets with simple integrations, giving you a working knowledge base in minutes.

The Cohere AI North platform and agentic AI

"North" is Cohere’s attempt to bundle its models into a secure AI workspace for employees. It’s designed to create "agentic AI", smart assistants that can automate entire tasks and figure out complex, multi-step problems on their own.

It sounds pretty futuristic, but "North" is a high-end, custom-built solution. They typically build it with massive clients, like the Royal Bank of Canada and Saudi Telecom. You can’t just buy it off the shelf and have your team using it by Friday.

Key use cases and target audience for Cohere AI

Figuring out who Cohere is for is the best way to know if it’s not for you. It all comes down to serving very large, very complex organizations.

The enterprise focus: Data privacy and flexible deployment

The big draw for huge companies is Cohere’s flexibility. You can run their models in your own private cloud or even on your own physical servers. This means your sensitive customer data never has to leave your control. They also don’t lock you into a single cloud provider, so you can use them on AWS, Microsoft Azure, Oracle Cloud, or whatever you prefer. For some companies, that level of control is a dealbreaker.

But for most support and IT teams, the real priority is a secure tool that’s just easy to manage. A tool like eesel AI strikes a more practical balance, offering enterprise-grade security, GDPR compliance, and optional EU data residency without making you manage the servers yourself.

In this video, Cohere's CEO Aidan Gomez explains the company's approach to improving AI reasoning and tackling hallucinations for enterprise use.

Vertical solutions for finance, telecom, and tech

Cohere’s strategy is all about forming deep partnerships with industry titans. They work hand-in-hand with companies like RBC in the finance world and STC in telecommunications to create custom, industry-specific AI tools.

This is a classic enterprise software sales model: long conversations, big contracts, and complex projects. It works great when you’re selling to a Fortune 500 company, but it’s a completely different universe from the fast, self-serve tools that most teams are looking for today.

Limitations and considerations of using Cohere AI

The tech behind Cohere is impressive, but there are some real-world limitations you need to think about before jumping in. These are often the reasons teams start looking for a more straightforward alternative.

The high complexity and resource requirements

Let’s be direct: Cohere AI is a platform for developers. To get any value from it, you need engineers to work with its APIs, build the user interfaces, and manage the whole setup. This isn’t something a support manager or IT lead can get running over a lunch break. That creates a huge barrier for any team that doesn’t have spare engineering resources to dedicate to a long-term internal AI project.

The ‘build’ platform vs. a ‘buy’ solution dilemma

This brings us to the fundamental choice every team faces: do you want to build or buy? Cohere gives you the architectural plans and high-end materials to build a custom AI solution, but you have to bring the construction crew. You’re responsible for everything, from the chat window your agents will type into, to the complex logic that decides how to handle a support ticket.

This is where a "buy" solution like eesel AI offers a totally different approach. It’s a complete platform, designed from the ground up for support teams and internal knowledge management. Instead of a box of parts, you get a fully customizable workflow engine, a simulation mode to test your AI on thousands of your past tickets, and simple integrations that get you up and running in minutes, not months. It’s a move-in-ready solution built for the people who actually have to use it every day.

Cohere AI pricing

Cohere’s pricing is built for developers using an API and for large companies signing big contracts, which means it’s not exactly straightforward. For their main business products like North, you have to book a demo and talk to their sales team to even get a price. That’s pretty standard for enterprise software, but it’s a pain for teams who just want to try something out and see if it fits.

For their API, Cohere does have public rates, which are usually based on "tokens" (tiny pieces of words). For example, some of their models might cost between $0.50 and $3.00 for every million tokens you send in, and between $1.50 and $15.00 for every million tokens the model sends back. The bottom line is, figuring out your costs can feel a bit like guesswork, especially when you’re just starting out.

Is Cohere AI the right tool for your team?

So, what’s the final verdict? Cohere AI is a powerful, secure, and incredibly flexible AI platform. For a huge company with a team of engineers and a mission to build a completely custom AI solution from scratch, it’s one of the best options out there. It gives developers the raw power they need to create something unique.

But for most teams, Cohere’s greatest strengths are also its biggest weaknesses. It’s a complex "build" platform, not a ready-to-go "buy" solution. The setup takes a long time, it requires specialized skills, and the pricing can be hard to predict.

The choice is pretty clear. If you have a team of developers ready to spend the next few months building a custom AI application, Cohere AI is a fantastic toolkit for the job.

But if you’re a leader in customer support, IT, or operations and your goal is to automate tickets, help your agents, and get your company’s knowledge organized now, a self-serve platform is a much faster way to get there. eesel AI offers a powerful, no-code solution that you can set up in a few minutes and test thoroughly before it ever interacts with a single customer.