The mass move to digital during the pandemic and the embrace of generative AI accelerated cloud adoption, and the trend hasn’t reversed. On the contrary, Gartner estimates that, in 2023, global end-user spending on public clouds will reach over $599 billion, up from $421 billion in 2021 and nearly $500 billion in 2022.
Not every enterprise has adjusted well to the new norm. One challenge they’re encountering is overspending; according to a recent Forrester report, a whopping 94% of companies say that they’ve experienced avoidable cloud expenses due to underused and overprovisioned resources, a lack of in-house talent to oversee cloud infrastructure and other related factors.
The intractable problem of keeping track of — and reducing — cloud spend spawned an entirely new market of tools, FinOps, designed to abstract away cloud orchestration and optimization tasks. Competition in the sector grows by the day, but one of the more successful ventures is Cast AI, which today announced that it raised $35 million in a Series B round led by Vintage Investment Partners with participation from Creandum and Uncorrelated Ventures.
The new cash brings Cast AI’s total raised to $73 million and will be put toward product development and growing the startup’s team of just over 100 employees, CEO Yuri Frayman says.
“Every startup has to answer a fundamental question in this economic environment: ‘Is our business going to massively grow and benefit from economic headwinds, or will we experience revenue contraction?,'” Frayman told TechCrunch in an email interview. “Many business-to-business software-as-a-service companies are experiencing contraction or slower growth as a result of cost reduction and efficiency programs by customers. Our business continues to grow rapidly because we save customers [money] on their cloud spend, improve performance and reliability and boost DevOps and engineering productivity.”
Cast AI was co-launched by Frayman, Leon Kuperman and Laurent Gil in 2019. The trio’s inspiration came from Zenedge, a cloud-based cybersecurity firm that Frayman, Kuperman and Gil previously co-founded (and which Oracle acquired in 2018), where they struggled to keep cloud costs under control as they scaled up the platform.
“While we got monthly statements full of individual line-item expenses, we had no realistic way to actually reduce those costs and optimize our cloud resources,” Frayman said. “We quickly realized that we weren’t alone.”
With Cast AI, Frayman and crew sought to build a tool that could automatically adjust cloud usage up and down while optimizing for cost and providing insights into how cloud resources — specifically Kubernetes clusters — were being actively provisioned.
Kubernetes, an open system for automating software deployment and management within environments called “containers,” is organized into clusters — collections of software-running machines. Cast connects to public clouds including AWS, Google Cloud Platform and Azure and uses models to analyze and autonomously tune these clusters across servers.
“We train our models on millions of utilization data points collected every 15 seconds, encompassing anonymized CPU and memory utilization in all global regions and across all cloud providers,” Frayman explained. “We’re able to predict lower future compute prices to impact future batch workload scheduling — kind of like searching for a cheaper flight on Kayak and booking a future date that’s cheaper. We also have customer-specific models around workload seasonality, which allows the Cast AI platform to be proactive, rather than purely reactive to current workload requirements.”
Cast AI competes with FinOps startups including Exostellar, which in September netted $15 million for its suite of tools designed to optimize “enterprise-level” cloud spend. CloudZero, ProsperOps, Finout, Vantage, Ternary and Zesty are just a few of the other companies competing for a slice of the budding FinOps segment, which is projected to be worth $2.75 billion by 2023.
“As enterprises become increasingly cloud native, our impact becomes more relevant to the C-Suite,” Frayman said. “Customers look to solutions from companies like Cast AI because they need an unbiased source of truth to help them navigate the FinOps problem. We don’t care if Google, Amazon or Microsoft make more money — we ultimately are responsible for customer savings, and that’s what we deliver.”