Cast AI Raises $108M to Optimize AI, Kubernetes and Cloud Workloads
Cast AI, a company specializing in optimizing AI and Kubernetes workloads through automation, has successfully raised $108 million in a Series C funding round. This significant investment will fuel the company's research and development efforts, as well as support its expansion into key markets like the U.S. and other regions. Sources indicate that this round places Cast AI's post-money valuation near unicorn status, approximately $900 million.
Focus on Efficiency
According to Yuri Frayman, Cast AI's CEO and co-founder, the company's core mission is to enhance efficiency in GPU utilization and compute resource management. By optimizing workload distribution across GPUs, Cast AI aims to enable the execution of more workloads with the existing infrastructure.
Rapid Growth and Expansion
The company's rapid growth is evident when compared to its previous funding round in November 2023, where it raised $35 million at a post-money valuation of $300 million. With a total of over $86 million raised prior to this latest round, Cast AI has demonstrated significant momentum in the market. Although officially based in Miami, Florida, Cast AI maintains a strong European presence, with a majority of its development activities located in Lithuania, Poland, Romania, and Bulgaria.
Extensive Customer Base
Over the past three years, Cast AI has amassed a customer base of 2,100, including notable companies such as Akamai, BMW, FICO, HuggingFace, NielsenIQ, and Swisscom. These organizations leverage Cast AI's technology to analyze their cloud and on-premise capacity, identifying optimal cost-performance ratios for distributing compute workloads. The platform integrates seamlessly with major cloud providers and other infrastructure solutions.
Addressing Resource Allocation Challenges
In an era marked by processor shortages for training and running AI models, the need for effective resource allocation has never been more critical. Cast AI's research indicates that, on average, only a fraction of CPUs (10%) and memory (23%) are utilized, with similar inefficiencies observed in GPU usage.
Strategic Partnerships
The Series C funding round, led by G2 Venture Partners and SoftBank Vision Fund 2, with participation from Aglaé Ventures, Hedosophia, Cota Capital, Vintage Investment Partners, Creandum, and Uncorrelated Ventures, highlights the company's strategic importance. Frayman emphasized that this funding places Cast AI alongside companies like OpenAI and Crusoe Energy, which are involved in the large-scale Stargate AI infrastructure project, further solidifying its position in the AI ecosystem. Cast AI already partners with and serves as a customer to many of these organizations.
Cast AI is actively collaborating with Crusoe Energy, integrating its technology into their stack, and partnering with SoftBank to improve efficiency in their AI datacenters. The company is also involved in the collaborative project between OpenAI and SoftBank to develop services in Japan, highlighting its commitment to partnering with the broader AI ecosystem.
From Kubernetes to AI
While Cast AI's initial focus was on Kubernetes workloads, the surge in AI-related activities has driven significant growth and interest from customers and investors. The company's experience in optimizing cloud costs for Kubernetes applications, stemming from the founders' previous venture, Zenedge, laid the foundation for its current capabilities.
Carl Fritjofsson, general partner at Creandum, noted that Cast AI has been developing AI-driven automation solutions for an extended period, positioning it as a pioneer in the field.
Source: TechCrunch