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Run:AI raises $30M Series B for its AI compute platform

Run:AI, a Tel Aviv-based company that helps businesses orchestrate and optimize their AI compute infrastructure, today announced that it has raised a $30 million Series B round. The new round was led by Insight Partners, with participation from existing investors TLV Partners and S Capital. This brings the company’s total funding to date to $43 million.

At the core of Run:AI’s platform is the ability to effectively virtualize and orchestrate AI workloads on top of its Kubernetes-based scheduler. Traditionally, it was always hard to virtualize GPUs, so even as demand for training AI models has increased, a lot of the physical GPUs often set idle for long periods because it was hard to dynamically allocate them between projects.

Image Credits: Run.AI

The promise behind Run:AI’s platform is that it allows its users to abstract away all of the AI infrastructure and pool all of their GPU resources — no matter whether in the cloud or on-premises. This also makes it easier for businesses to share these resources between users and teams. In the process, IT teams also get better insights into how their compute resources are being used.

“Every enterprise is either already rearchitecting themselves to be built around learning systems powered by AI, or they should be,” said Lonne Jaffe, managing director at Insight Partners and now a board member at Run:AI.” Just as virtualization and then container technology transformed CPU-based workloads over the last decades, Run:AI is bringing orchestration and virtualization technology to AI chipsets such as GPUs, dramatically accelerating both AI training and inference. The system also future-proofs deep learning workloads, allowing them to inherit the power of the latest hardware with less rework. In Run:AI, we’ve found disruptive technology, an experienced team and a SaaS-based market strategy that will help enterprises deploy the AI they’ll need to stay competitive.”

Run:AI says that it is currently working with customers in a wide variety of industries, including automotive, finance, defense, manufacturing and healthcare. These customers, the company says, are seeing their GPU utilization increase from 25 to 75% on average.

“The new funds enable Run:AI to grow the company in two important areas: first, to triple the size of our development team this year,” the company’s CEO Omri Geller told me. “We have an aggressive roadmap for building out the truly innovative parts of our product vision — particularly around virtualizing AI workloads — a bigger team will help speed up development in this area. Second, a round this size enables us to quickly expand sales and marketing to additional industries and markets.”

Run.AI raises $13M for its distributed machine learning platform



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