Nvidia's $700 million acquisition of Run:ai stalled by lengthy regulatory review
Administrative changes made by the American regulator have resulted in the deal being examined only now, which may lead to a significant delay in its completion. It is estimated that the deal will eventually be completed, but long after the originally scheduled date.
The purchase of the Israeli artificial intelligence company Run:ai by Nvidia is facing a significant delay. Calcalist has learned that administrative changes made by the American regulator have resulted in the deal being examined only now, which may lead to a lengthy delay in its completion. It is estimated that the deal will eventually be completed, but long after the originally scheduled date.
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Nvidia officially announced its intent to acquire the AI infrastructure orchestration and management platform back in April. The value of the deal was not revealed, but is estimated at around $700 million.
“Run:ai has been a close collaborator with NVIDIA since 2020 and we share a passion for helping our customers make the most of their infrastructure,” said at the time Omri Geller, Run:ai co-founder and CEO. “We’re thrilled to join NVIDIA and look forward to continuing our journey together.”
The purchase of Run:ai is set to be Nvidia’s biggest acquisition in Israel since purchasing Mellanox for $6.9 billion in March 2019. Since the acquisition, Nvidia’s local R&D center in Israel, which was first established in 2016, grew by about 100%, reaching 4,000 employees in the country. Shortly after the Run:ai announcement, Nvidia also revealed it was purchasing Israeli AI company Deci in a deal estimated at around $300 million.
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Run:ai raised $75 million in a Series C round in March 2022 led by Tiger Global Management and Insight Partners, who also led the previous Series B round. The round included the participation of additional existing investors, TLV Partners, and S Capital VC, bringing the total funding raised to date to $118 million.
Run:ai was founded in 2018 by Omri Geller (CEO) and Dr. Ronen Dar (CTO). Run:ai has developed an orchestration and virtualization software layer tailored to the unique needs of AI workloads running on GPUs and similar chipsets. Run:ai’s Kubernetes-based container platform for AI clouds efficiently pools and shares GPUs by automatically assigning the necessary amount of computing power – from fractions of GPUs, to multiple GPUs, to multiple nodes of GPUs.
