In a sign that there’s plenty of cash to go around for generative AI startups, Cohere, which is developing an AI model ecosystem for the enterprise, today announced that it raised $270 million as part of its Series C round.
Reuters reported earlier in the year that Cohere was in talks to raise “hundreds of millions” of dollars at a valuation of upward of just over $6 billion. If there’s credence to that reporting, Cohere appears to have missed the valuation mark substantially; a source familiar with the matter tells TechCrunch that this tranche values the company at between $2.1 billion and $2.2 billion.
“The new capital will fuel continued development of Cohere’s AI platform, which is focused on enterprise customers, allowing companies to use their preferred cloud provider to increase data privacy and make implementation simpler,” president and COO Martin Kon told TechCrunch via email. “The latest round allows us to invest in compute, grow our team, engage with more of the world’s leading enterprises and further advance our world-leading AI, ultimately empowering companies to build incredible products while keeping their data private and secure.”
Aidan Gomez, Ivan Zhang and Nick Frosst (who was one of the first employees at Google’s Toronto AI lab) co-founded Cohere in 2019. Before starting Cohere, Gomez co-authored the seminal paper “Attention Is All You Need,” which introduced the Transformer, the architecture behind popular large language models (LLMs) like OpenAI’s GPT-4.
Kon joined in early 2023, jumping from his previous role as CFO at YouTube.
Cohere, which has developed multilingual language models trained on data from native speakers, among other AI, aims to stand out in the ocean of generative AI startups by focusing on enterprise use cases.
Cohere’s AI platform is cloud agnostic, able to be deployed inside public clouds (e.g., Google Cloud, Amazon Web Services), a customer’s existing cloud, virtual private clouds or on-site. The startup takes a hands-on approach, working with customers to create custom LLMs based on their proprietary data.
“Cohere was founded to create a platform that empowers all enterprises to transform their company and products with world-leading AI that’s cloud-agnostic, accessible, customizable and data-secure,” Kon said. “Our mission is to allow enterprises worldwide to leverage this transformational technology.”
Cohere holds its customer numbers close to its chest. But the startup claims that it works with companies like Jasper and HyperWrite for copywriting generation tasks like creating marketing content, drafting emails and developing product descriptions. Elsewhere, Cohere recently announced a collaboration with LivePerson, the conversational marketing company, to build fine-tuned LLMs to improve explainability. And the startup’s partnering with a handful of organizations, including news outlets and Salesforce Ventures, to help break down, analyze and summarize lengthy text using machine learning algorithms.
“Generally, we can share that we’re experiencing high demand from major enterprises, as both customers and partners,” Kon said.
Cohere, which has around 180 employees, has raised a lot of capital — $445 million — even by generative AI startup standards. Only OpenAI ($11.3 billion) and Anthropic ($450 million) have raised more, ahead of rivals Inflection AI ($225 million) and Adept ($415 million).
“When it comes to AI, building and training language models requires a lot of capital, but we’re mindful and intentional about what we actually need and committed to securing funds that will ensure we can continue providing the best possible solution for our customers,” Kon said. “We’ve been intentional about maintaining a diversity of global investors and not taking one bigger check from one company — especially a cloud provider — because that may limit our ability to remain independent, service enterprises directly, remain cloud-agnostic and deploy data-secure solutions on any cloud according to our customers’ preference.”
That comment about cloud provider investments was a likely dig at startups like OpenAI and Anthropic, which have taken on significant backing from Microsoft and Google, respectively. But it’s curious coming from Cohere, which not long ago was reportedly in advanced talks with Google about an investment in the range of $200 million.
Regardless of where its future capital comes from, Kon says he sees “search and retrieval” as the next core area of growth for Cohere. Using techniques that give models or chatbots the ability to expand on their knowledge base and search the web for information that’s relevant to a query, like OpenAI’s experimenting with, Kon believes that Cohere can build significantly more powerful AI systems than it offers today.
“Today, chatbots don’t have access to the world. They don’t know about what happened 10 minutes ago. They have to memorize everything within themselves, and they only have memory of what they saw during training,” Kon said. “With search and retrieval, you can require a model to cite sources, so users don’t need to blindly trust a model; everything links out to a site that you can verify and fact check.”
Looking further ahead, Cohere plans to build models that can take action and “do work” for customers, like book a flight, schedule a meeting or file an expense report on a person’s behalf. In that way, it’s chasing after competitors like Adept, Inflection and OpenAI, all of which are building — albeit using different approaches — systems to connect AI with third-party apps, services and products.
Despite the competition, Kon asserts that Cohere’s in a position of strength.
“We’re differentiated as the independent, cloud-agnostic AI platform for enterprises,” he said. “We are solely focused on enabling our customers to create proprietary LLM capabilities leveraging their data and creating strategic differentiation and business value.”
Inovia Capital led the oversubscribed Series C round with participation from Nvidia, Oracle, Salesforce Ventures, DTCP, Mirae Asset, Schroders Capital, SentinelOne, Thomvest Ventures and Index Ventures.
Comment