Cohere co-founder sees big AI opportunity in enterprise, happy to stay out of ChatGPT’s way
Omar Marques | Lightrocket | Getty Images
Cohere co-founder Nick Frosst is surrounded by chatter of artificial general intelligence, or AGI. He’s perfectly happy to stay out of the conversation.
Founded in 2019, by ex-Google AI researchers, Cohere is valued in the billions of dollars and is one of the more high-profile names in the world of generative AI, which has exploded since OpenAI debuted ChatGPT in late 2022.
But it’s not a company that’s well known among consumers, who have swarmed to chatbots and other tools from OpenAI, Google and Perplexity. Rather, Cohere is all about business.
“I’m in meetings with companies in health care, banking and IT all the time,” Frosst told CNBC in an interview this week. “The questions I get are about securely automating tasks like HR, payrolls, research and fraud detection to drive productivity. No one has ever asked me about achieving AGI, let alone ASI.”
The latter is short for artificial superintelligence, or AI that significantly surpasses human intelligence. OpenAI and Anthropic have both made it their goal to achieve it.
In its latest funding round in July, Cohere raised $500 million at a $5.5 billion valuation, more than doubling its valuation from the prior year. Investors in the company include Nvidia, AMD, Salesforce and Oracle.
While that would historically be a huge price tag for a company that’s not even five years old, it’s a fraction of what investors are paying for OpenAI, valued at $157 billion in a round announced in October, and Anthropic, which CNBC confirmed this week is in talks to raise funding at a $60 billion valuation.
Some of Cohere’s chief competitors in the AI arms race offer products for both consumers and businesses. OpenAI, for instance, launched ChatGPT Enterprise in 2023, and Anthropic rolled out Claude Enterprise in September.
Frosst said Cohere’s preference for the enterprise is centered around the idea that large language models are best at automating tedious tasks and “being a co-worker.”
“Really, it’s an automation tool,” Frosst said. “When I think about my personal life, there’s actually not a ton that I want to automate. I don’t want to write text messages to my friends faster. I don’t want to respond to emails more efficiently in my own life. But in my work life, I really, really do want to do that.”
Frosst said, “I want to be free to think creatively and not be bogged down.”
Shortly after closing its funding round in July, Cohere cut about 20 jobs. A company representative said at the time it was an “internal realignment” and that Cohere had a “clear vision for the future.”
That vision includes going all-in on AI agents.
While the term AI agents isn’t neatly defined, it’s generally meant to describe AI services that go a step beyond chatbots. Agents are typically designed for specific business functions, rather than general purpose, and can be customized on the big AI models.
They can perform multistep, complex tasks on a user’s behalf and generate their own to-do lists, so that users don’t have to walk them through the process step-by-step.
Staying capital efficient
On Thursday, Cohere debuted its early access program for its AI agent platform called North, which is focused on allowing users with any level of technical background to “instantly customize and deploy AI agents” and do so “with just a few clicks,” the company said in a press release. Users can search for information across their organizations in multiple languages and in divisions with programs that weren’t previously connected.
That includes summarizing questions and answers in HR, speeding up the amount of time spent on finance reports and automating some core business functions in customer support and IT.
Frosst said that the platform can be used in any industry, but the company plans to target finance and health care, where data privacy and regulation are paramount.
Martin Kon, Cohere’s operating chief, told CNBC in March that by staying focused on enterprise AI, the company is able to run efficiently and keep expen under control even amid a chip shortage, rising costs for Nvidia’s graphics processing units (GPUs) and ever-changing licensing fees for AI models.
Frosst says those dynamics are still at play, allowing Cohere to be “more capital-efficient,” which is increasingly “of interest to investors.” Rivals with popular consumer-facing AI products, he said, use a lot of compute on “consumer applications and science projects.”
Although the sales cycle for enterprise AI can be longer, Frosst said, “the recurring business we’ve been able to create is something that’s really resonating with investors now.”
Competition is stiff and the technology is quickly evolving.
In October, Anthropic said its AI agents had the ability to use a computer like a human would in order to complete complex tasks. The feature, called Computer Use, allows its technology to interpret what’s on a computer screen, select buttons, enter text, navigate websites and execute tasks through any software and real-time internet browsing.
OpenAI reportedly plans to introduce a similar feature soon. And last year, executives from Microsoft, Meta and Google regularly touted their goals to push AI assistants to become increasingly productive.
Even without a consumer business, Cohere has to spend heavily on Nvidia’s costly GPUs, which are in huge demand for companies that are training models and running big workloads. In Cohere’s early days, the company secured a reserve of Google chips to help it pretrain its models. Over the past year, Cohere has moved more toward Nvidia’s H100 GPUs.
“We’ve increased our spend on them, because they’re working really well,” Frosst said.
WATCH: Cohere CEO Aidan Gomez on how his AI models make money for companies
Jensen Huang, chief executive officer of Nvidia Corp., during the US-Saudi Investment Forum at the Kennedy Center in Washington, DC, US, on Wednesday, Nov. 19, 2025.
Stefani Reynolds | Bloomberg | Getty Images
In the weeks leading up to Nvidia’s third-quarter earnings report, investors debated whether the markets were in an AI bubble, fretting over the massive sums being committed to building data centers and whether they could provide a long-term return on investment.
During Wednesday’s earnings call with analysts, Nvidia CEO Jensen Huang began his comments by rejecting that premise.
“There’s been a lot of talk about an AI bubble,” Huang said. “From our vantage point we see something very different.”
In many respects, Huang’s remarks are to be expected. He’s leading the company at the heart of the artificial intelligence boom, and has built its market cap to $4.5 trillion because of soaring demand for Nvidia’s graphics processing units.
Huang’s smackdown of bubble talk matters because Nvidia counts every major cloud provider — Amazon, Microsoft, Google, and Oracle — as a customer. Most of the major AI model developers, including OpenAI, Anthropic, xAI and Meta, are also big buyers of Nvidia GPUs.
Huang has deep visibility into the market, and on the call he offered a three-pronged argument for why we’re not in a bubble.
First, he said that areas like data processing, ad recommendations, search systems, and engineering, are turning to GPUs because they need the AI. That means older computing infrastructure based around the central processor will transition to new systems running on Nvidia’s chips.
Second, Huang said, AI isn’t just being integrated into current applications, but it will enable entirely new ones.
Finally, according to Huang, “agentic AI,” or applications that can run without significant input from the user, will be able to reason and plan, and will require even more computing power.
In making the case of Nvidia, Huang said it’s the only company that can address the three use cases.
“As you consider infrastructure investments, consider these three fundamental dynamics,” Huang said. “Each will contribute to infrastructure growth in the coming years.”
Reversing the slide
In its earnings release, Nvidia reported revenue and profit that sailed past estimates and issued better-than-expected guidance. Last month, Huang provided a $500 billion forecast for sales of the company’s AI chips over calendar 2025 and 2026.
The company said on Wednesday that its order backlog didn’t even include a few recent deals, like an agreement with Anthropic that was announced this week or the expansion of a deal with Saudi Arabia.
“The number will grow,” CFO Colette Kress said on the call, saying the company was on track to hit the forecast.
Prior to Wednesday’s results, Nvidia shares were down about 8% this month. Other stocks tied to the AI have gotten hit even harder, with CoreWeave plunging 44% in November, Oracle dropping 14% and Palantir falling 17%.
Some of the worry on Wall Street has been tied to the debt that certain companies have used to finance their infrastructure buildouts.
“Our customers’ financing is up to them,” Huang said.
Specific to Nvidia, investors have raised concerns in recent weeks about how much of the company’s sales were going to a small number of hyperscalers.
Last month, Microsoft, Meta, Amazon and Alphabet all lifted their forecasts for capital expenditures due to their AI buildouts, and now collectively expect to spend more than $380 billion this year.
Huang said that even without a new business model, Nvidia’s chips boost hyperscaler revenue, because they power recommendation systems for short videos, books, and ads.
People will soon start appreciating what’s happening underneath the surface of the AI boom, Huang said, versus “the simplistic view of what’s happening to capex and investment.”
WATCH: Nvidia posts Q3 beat
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