Cast AI Secures $108M to Optimize AI & Kubernetes Workloads
▼ Summary
– Cast AI, a Miami-based startup, raised $108 million in Series C funding to enhance its platform for optimizing AI and Kubernetes workloads, reaching a $900 million valuation due to rising demand for efficient resource allocation.
– The company addresses inefficiencies in cloud usage, revealing that enterprises often utilize only 10% of CPU capacity and 23% of memory, leading to significant cost savings for clients like BMW and Akamai.
– Cast AI’s strategic partnerships include collaborations with Crusoe Energy and SoftBank, contributing to projects like OpenAI’s Stargate and Japan’s AI service rollout, with investors such as Aglaé Ventures joining the funding round.
– The team, with a history in optimizing GPU workloads, uses its Kubernetes optimization technology to address cloud cost issues, with the AI boom accelerating its adoption.
– The new funding will support R&D and U.S. expansion, as Cast AI aims to tackle challenges like GPU scarcity and energy costs, positioning itself as a leader in efficient AI infrastructure scaling.
Managing cloud costs while scaling AI workloads has become a critical challenge for enterprises worldwide. Cast AI, a Miami-based startup with deep European roots, just secured $108 million in Series C funding to expand its automated optimization platform for AI and Kubernetes workloads. The round, co-led by G2 Venture Partners and SoftBank Vision Fund 2, propels the company toward a $900 million valuation as demand surges for efficient GPU and compute resource allocation.
“The bottleneck isn’t just hardware—it’s waste,” explains CEO Yuri Frayman. Cast AI’s research reveals staggering inefficiencies: enterprises typically use just 10% of CPU capacity and 23% of memory, even as AI projects strain budgets. The platform dynamically redistributes workloads across clouds and on-prem systems, slashing costs for clients like BMW, Akamai, and Hugging Face.
The funding signals strategic alignment with major AI infrastructure players. Cast AI already collaborates with Crusoe Energy and SoftBank—key partners in OpenAI’s Stargate project—and is embedded in Japan’s AI service rollout. Aglaé Ventures (backed by LVMH’s Bernard Arnault) joined existing investors like Creandum and Vintage Investment Partners in this oversubscribed round.
Frayman’s team has been optimizing GPU workloads since their early ML startup Viewdle (acquired by Google in 2012). Their later venture, Zenedge, exposed the cloud cost crisis that inspired Cast AI’s core Kubernetes optimization tech. While Kubernetes remains its revenue backbone, the AI boom has accelerated adoption.
“They pioneered autonomous cloud agents before it was trendy,” notes Creandum’s Carl Fritjofsson. With AI-driven infrastructure demands doubling annually, Cast AI’s timing couldn’t be better. The new capital will fuel R&D and U.S. expansion, helping enterprises tackle what Frayman calls the “triple crisis of GPU scarcity, energy costs, and compute sprawl.”
SoftBank’s Tim Yap summarizes the bet: “Efficiency is the next frontier in AI scaling, and Cast AI is defining it.” As models grow more complex, the startup’s automation could decide which companies stay competitive—and which drown in cloud bills.
(Source: TechCrunch)
