Nvidia has finalized its acquisition of Run:ai, a company located in Tel Aviv that simplifies the management and enhancement of AI hardware infrastructure for developers and operational teams.

Nvidia is spending $700 million for this transaction, though the cost could go higher following advanced talks. This information is not publicly available but was shared by insiders available to TechCrunch.

CTech revealed that the two companies were in the final stages of negotiation, with Nvidia potentially spending over $1 billion to acquire Run:ai. It appears the discussions concluded smoothly, with only a potential adjustment in the final price.

Nvidia has announced that it will maintain Run:ai’s current product offerings under the existing business model and will continue to develop Run:ai’s product lineup as a component of its DGX Cloud AI platform. This platform provides enterprise clients with the necessary computing infrastructure and software to train generative and other types of AI models.

Additionally, customers of Nvidia’s DGX server, workstation, and DGX Cloud will benefit from the integration of Run:ai’s technologies, particularly for managing generative AI operations across various data center sites, according to Nvidia.

Omri Geller, Run:ai’s CEO, said in a statement: “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. We’re thrilled to join Nvidia and look forward to continuing our journey together.”

Several years ago, Geller and Ronen Dar, who studied together at Tel Aviv University under Professor Meir Feder, co-founded Run:ai. Professor Feder also joined as the third co-founder. Their goal was to develop a platform capable of dividing AI models into fragments that could operate simultaneously across various hardware setups, whether located on-premises, in public clouds, or at the edge.

Although Run:ai faces limited direct competition, other companies utilize similar approaches to managing AI workloads. For instance, Grid.ai provides software that enables data scientists to simultaneously train AI models using multiple GPUs, processors, and other resources.

Before being acquired, Run:ai secured $118 million in funding from investors such as Insight Partners, Tiger Global, S Capital, and TLV Partners.

On the other hand, Nvidia has recently unveiled the world’s most powerful AI GPUs for model training dubbed the Blackwell GPUs. Meanwhile, competitors including Huawei have also announced their rival offerings against Nvidia’s lower-tier A100 GPUs.