Cast AI raises $108M to get the most out of AI, Kubernetes and other workloads
The crush of traffic going into training and running AI has quickly turned into a major cost and resource headache for organizations. Today, Cast AI, a startup building tools to ease and optimize workloads for AI and other tasks with automation, is raising a major round of funding on the back of strong growth and partnerships with major players in the space.
The company has raised a $108 million Series C that it will be using both for more R&D as well as to expand its business in core markets like the U.S. and elsewhere. Sources familiar with the deal told TechCrunch that the round has the company at “near unicorn” valuation, post-money — close to $900 million from what I understand.
“It’s all about GPU, compute and electricity,” said Yuri Frayman, Cast’s CEO and co-founder. “Our play is to ensure that we create efficiency, to be able to promote more workloads across GPUs. That is what we are about.”
For context, when Cast last raised capital, $35 million in November 2023, it was valued at $300 million post-money, per PitchBook. Prior to this latest round, the startup had raised just over $86 million.
Cast AI is based out of Miami, Florida, but “is heavily situated in Europe” and Frayman describes it as “a European company,” with most of its development done in Lithuania, Poland, Romania and Bulgaria.
It has amassed 2,100 customers in the last three years of business. Companies like Akamai, BMW, FICO, HuggingFace, NielsenIQ and Swisscom are among those using its technology to analyse cloud and on-premise capacity and find the optimal cost-performance ratio for distributing compute workloads across them. Frayman says it integrates with all major cloud providers and anything else that a customer may be using.
At a time where companies are facing a shortage of processors to train and run AI models, there’s a strong need for better resource allocation. Cast AI, citing its own research, claims that on average only 10% of CPUs and 23% of memory are utilized, and the same extends to GPU usage.
This Series C — both in size and participants — underscores what else the startup is working on, and whom else it is working with.
G2 Venture Partners and SoftBank Vision Fund 2 are co-leading the round. Aglaé Ventures (LVMH chairman and CEO Bernard Arnault’s investment firm), and previous backers Hedosophia, Cota Capital, Vintage Investment Partners, Creandum, and Uncorrelated Ventures are also participating.
Notably, Frayman pointed out that the oversubscribed round puts the company in the same portfolio stable as OpenAI and AI infrastructure provider Crusoe Energy — two companies that are, with SoftBank, Oracle and others, working on the massive Stargate AI infrastructure project in the U.S.
Frayman said his company counts a number of these companies as partners and customers already. “We are partnering with Crusoe, where we’re inside their stack, and we are partnering with SoftBank to be able to facilitate the efficiency in their AI datacenters,” he said, adding that the startup is also part of the large project between OpenAI and SoftBank to build services in Japan. “We are partnering with the entire ecosystem,” he added.
Cast AI is talking and doing a lot with AI these days, but that was not where the company got its start. Ukraine-born Frayman, who founded the company with Leon Kuperman and Laurent Gil in 2019, started his career in finance before pivoting to software development.
Back in 2006, he and Gil built what Frayman described as one of the “earliest machine learning startups,” Viewdle. There, they built some of the earliest applications that used Nvidia GPUs to train classifiers for image searches. “That’s how far back we go in terms of understanding the power of machine learning,” he said.
That company would eventually get acquired by Google.
The three founders later worked on a cloud-based cybersecurity startup, Zenedge, which was the inspiration for Cast — they were struggling to keep cloud costs under control as they scaled up. (Zenedge was eventually acquired by Oracle.)
The first use case for Cast AI was born from their experience with that resource struggle. While Cast has always had “AI” in its name and ethos, it was about its application, specifically making cloud use and allocation more efficient for Kubernetes workloads.
Kubernetes applications are still at the heart of the startup, Frayman said, both in terms of revenue and ethos (if you visit its site, you’ll see prominent messaging there, too). But it is the surge of activity around AI where all the buzz and growth are flowing from — both customers and investors.
“Cast AI is setting a new standard for cloud efficiency at a time when infrastructure demands are surging,” said Tim Yap, investment director at SoftBank Investment Advisers, in a statement.
“Right now in the world, everyone is talking about AI agents,” said Carl Fritjofsson, general partner at Creandum. “Cast was an AI agent before we started talking about that technology, you know. They’ve just been building this type of automation for a long time.”