Home » Cast AI, which helps companies optimize cloud spend, lands $35M

Cast AI, which helps companies optimize cloud spend, lands $35M

by Alex Turner
Image Credits: baranozdemir / Getty Images

The widespread adoption of digital during the pandemic and the acceptance of generative AI increased cloud use, and this tendency hasn’t changed. Quite the reverse; according to Gartner, end-user expenditure on public clouds will grow to over $599 billion globally in 2023 from $421 billion in 2021 and almost $500 billion in 2022.

Not every business has successfully adapted to the new standard. Overspending is one issue they’re facing; a recent Forrester study found that an astounding 94% of companies claim to have incurred avoidable cloud expenses as a result of underutilized and overprovisioned resources, a shortage of internal talent to manage cloud infrastructure and other related issues.

Get Posts Like This Sent to your Email
Iterative approaches to corporate strategy foster collaborative thinking to further the overall value.
Get Posts Like This Sent to your Email
Iterative approaches to corporate strategy foster collaborative thinking to further the overall value.

FinOps, a whole new product market created to abstract away cloud orchestration and optimization activities, was born out of the unmanageable challenge of tracking and minimizing cloud costs. Amidst the increasing competition in the industry, Cast AI has emerged as a very prosperous initiative. The business recently disclosed that it had raised $35 million in a Series B round, with Vintage Investment Partners as the lead investor and Creandum and Uncorrelated Ventures participating.

With this additional funding, Cast AI has raised $73 million. According to CEO Yuri Frayman, the funds will be used for product development and expanding the startup’s staff of slightly over 100 people.

In the current economic climate, “every startup needs to respond to a basic question: ‘Will our business experience revenue contraction or will it grow massively and benefit from economic headwinds?'” In an email interview, Frayman revealed this to TechCrunch. Many business-to-business software-as-a-service providers are seeing a slowdown in growth or contraction due to client efficiency and cost-cutting initiatives. Because we save clients money on their cloud expenditures, enhance performance and dependability, and increase DevOps and engineering efficiency, our business is expanding quickly.

In 2019, Frayman, Leon Kuperman, and Laurent Gil co-launched Cast AI. The three drew inspiration from their experiences growing Zenedge, a cloud-based cybersecurity company that Frayman, Kuperman, and Gil had previously co-founded and that Oracle acquired in 2018. There, they had difficulty controlling cloud expenses.

Frayman stated, “Even though we received monthly statements with detailed line-item expenses, we lacked a practical method to truly cut those costs and maximize our cloud resources.” “We discovered very quickly that we weren’t alone.”

Frayman and his team set out to create Cast AI to create a platform that could automatically scale up and down cloud consumption while optimizing for cost and providing insights into the active provisioning of cloud resources, particularly Kubernetes clusters.

Clusters are groups of computers running software that are part of Kubernetes, an open framework for automating software deployment and administration within environments known as “containers.” Through its connections to public clouds such as AWS, Google Cloud Platform, and Azure, Cast analyzes and tunes these clusters across servers autonomously using models. The dashboard for optimizing cloud consumption and budget using Cast AI. Picture courtesy of Cast AI

“Our models are trained using millions of utilization data points that are gathered every 15 seconds, which include anonymized CPU and memory utilization across all cloud providers and global regions,” Frayman said. We may forecast reduced computation costs to influence batch task scheduling. It’s similar to using Kayak to find a less expensive trip and rescheduling it for a later time. Additionally, the Cast AI platform may be proactive rather than only reactive to the demands of the present workload because we have customer-specific models for workload seasonality.

Cast AI faces competition from FinOps firms such as Exostellar, which raised $15 million in September for its suite of solutions to optimize cloud spending at the “enterprise-level.” A few of the other businesses vying for a piece of the emerging FinOps market—which is expected to be valued at $2.75 billion by 2023—are CloudZero, ProsperOps, Finout, Vantage, Ternary, and Zesty.

However, Frayman argues that there is a surplus of demand for FinOps solutions, which is advantageous for Cast AI. And he may be in error. Wakefield Research from 2023 states that over three out of ten developers, engineers, and executives plan to prioritize FinOps expenditures this year. According to 74% of the participants, FinOps is now considered equally significant as other well-known IT specialties like SecOps and DevOps.
“Our impact becomes more relevant to the C-Suite as enterprises become more cloud-native,” Frayman stated. To handle the FinOps dilemma, customers turn to firms like Cast AI for their solutions since they require an objective source of truth. We are ultimately in charge of ensuring that customers save money, and we do that regardless of how much money Google, Amazon, or Microsoft make.

You may also like

Leave a Comment