Is Your Cloud Spending Out of Control? Discover the AI Startup Revolutionizing Cost Reduction by Halving Your Expenses.

Miami-based Cast AI, a startup leveraging machine learning to help enterprises manage and optimize their cloud expenses, today announced a successful $35 million Series B funding round.

Led by Vintage Investment Partners, this investment will enhance Cast AI's AI capabilities, providing enterprise teams with a robust solution for real-time cost tracking and optimization. The platform automates the previously manual resource management tasks, effectively reducing operational costs.

“Every single person at Cast AI is dedicated to helping customers reduce their cloud spending by automating tasks best suited for machine learning,” said Yuri Frayman, co-founder and CEO of Cast AI. “This commitment is why our customer growth continues to soar, attracting marquee clients.”

Automating Kubernetes Clusters to Lower Cloud Costs

As digital transformation accelerates, companies across industries are modernizing applications and migrating to the cloud. However, many teams struggle to manage escalating cloud costs as application demands grow—from thousands to millions of dollars due to resource mismanagement.

Recognizing this challenge, the founders of Cast AI—Yuri Frayman, Leon Kuperman, and Laurent Gil—previously involved in the Oracle-acquired cybersecurity platform Zenedge, shifted their focus to AI-driven optimization. They aimed to develop advanced solutions that would automate resource management instead of relying on manual adjustments.

“We quickly realized this was a universal challenge,” said Gil, Cast’s chief product officer. “Our mission at Cast AI was to create the product we wish we had at Zenedge—an advanced AI platform capable of real-time resource scaling and cost optimization.”

Trusted Solutions for Leading Enterprises

Founded in 2019, Cast AI has garnered a clientele that includes industry leaders like Akamai, Yotpo, Sharechat, Rollbar, Switchboard, and EVgo. The platform serves as an all-in-one solution, employing advanced ML algorithms to optimize Kubernetes clusters while providing comprehensive visibility into resource allocation.

Kubernetes (often abbreviated as K8s) automates the deployment and management of containerized applications across on-premises and cloud infrastructures. Cast AI enhances this process by integrating with major cloud partners such as Google Cloud, AWS, and Azure to analyze and optimize these clusters automatically.

This sophisticated tuning enables enterprises to achieve savings of 50% or more on cloud expenditures while improving performance and DevOps productivity. For example, Iterable, one of Cast AI's clients, successfully reduced its annual cloud costs by over 60%, resulting in savings of $3-4 million annually.

Future Developments on the Horizon

With the latest funding bringing Cast AI's total capital raised to $73 million, the company plans to expand its offerings to automate additional aspects of Kubernetes optimization. Recently, it launched two new features: Workload Rightsizing and PrecisionPack.

Workload Rightsizing automates near real-time scaling of workload requests, ensuring both performance and cost-efficiency. PrecisionPack, a next-generation Kubernetes scheduling feature, uses an advanced bin-packing algorithm to optimize pod placement across designated nodes, enhancing resource utilization and operational predictability.

While Cast AI is a strong player in the FinOps space—tools designed to reduce cloud spending—it faces competition from other emerging companies like CloudZero, Zesty, and Exostellar, all of which are garnering substantial venture capital support.