Nvidia acquires AI workload management startup Run:ai

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Nvidia is acquiring Run:ai, a Tel Aviv-based company that makes it easier for developers and operations teams to manage and optimize their AI hardware infrastructure, for an undisclosed amount.

Ctech reported early this morning that the two companies are in “advanced negotiations” and that Nvidia could pay more than $1 billion for Run:ai. It appears that the negotiations went smoothly.

Sources told TechCrunch that the exact price was $700 million.

Nvidia says it will continue to offer Run:ai’s products “with the same business model” and will invest in Run:ai’s product roadmap as part of Nvidia’s DGX Cloud AI platform. This gives enterprise customers access to cloud computing infrastructure and software. Use to train models for generative and other forms of AI. According to Nvidia, Nvidia DGX Servers and Workstations and DGX Cloud customers will now have access to Run:ai capabilities for AI workloads, particularly generative AI deployments that run across multiple data centers. Masu.

“Run:ai has worked closely with Nvidia since 2020 and we share a passion for helping customers get the most out of their infrastructure,” said Omri Geller, CEO of Run:ai. stated in a statement. “We are excited to have him join Nvidia and look forward to continuing our journey together.”

Geller co-founded Run:ai several years ago with Ronen Dahl after studying with Run:ai’s third co-founder, Professor Meir Feder, at Tel Aviv University. . Geller, Dahl, and Feder aimed to build a platform that could “split” AI models into pieces that could run in parallel on hardware, whether on-premises, in the public cloud, or at the edge.

While Run:AI has relatively few direct competitors, other startups are applying the concept of dynamic hardware allocation to AI workloads. For example, Grid.ai offers software that allows data scientists to train AI models in parallel across GPUs, processors, and more.

However, Run:AI was able to establish a large customer base of Fortune 500 companies relatively early on, which attracted VC investment. Prior to the acquisition, Run:ai had raised $118 million in funding from backers including Insight Partners, Tiger Global, S Capital, and TLV Partners.

Alexis Bjorlin, Nvidia’s vice president of DGX Cloud, said in a blog post that customers’ AI deployments are becoming increasingly complex and enterprises are increasingly demanding more efficient use of AI computing sources. I said that.

“Managing and orchestrating generative AI, recommender systems, search engines, and other workloads requires sophisticated scheduling to optimize system-level and underlying infrastructure performance,” he said. Masu. “Nvidia’s accelerated computing platform and Run:ai’s platform continue to support a broad ecosystem of third-party solutions, providing customers with choice and flexibility. , giving customers a single fabric to access GPU solutions from anywhere.”

Run:ai is one of Nvidia’s biggest acquisitions since acquiring Mellanox in March 2019 for $6.9 billion.