Nebius and NVIDIA collaborate for physical AI cloud

Nebius Group N.V. and NVIDIA Corp. claim to have solved robotics development’s “three-computer problem,” where engineering teams waste up to 40% of their time stitching together incompatible systems. The companies have partnered to offer an integrated cloud platform that handles everything from AI training to edge deployment for robot developers.

“Physical AI is going to be one of the defining technology shifts of this decade, and the teams building it today are being held back by infrastructure and tooling that was never designed for those workloads,” said Evan Helda, head of physical AI at Nebius. “Working with NVIDIA, we are building the execution layer for the entire physical AI ecosystem — so that any team, anywhere, can go from idea to deployed robot at the speed the market demands.”

NVIDIA is presenting its annual GTC user conference this week in San Jose, Calif. Earlier this month, NVIDIA also announced that it is investing $2 billion in Nebius, reflecting its confidence in the Amsterdam-based company‘s business and engineering expertise across the full AI technology stack.

“Physical AI is the next phase of computing — where intelligence is trained, tested and validated in simulation before it operates in the real world,” stated Rev Lebaredian, vice president of Omniverse and simulation technologies at NVIDIA. “That demands tightly integrated systems connecting large-scale AI training with physically accurate simulation to create a continuous data flywheel. By integrating the NVIDIA Physical AI Data Factory Blueprint, Nebius is enabling developers to generate physics-grounded synthetic data and build safe, robust autonomous machines at scale.”

NVIDIA and Nebius integrate key technologies

The new platform integrates the NVIDIA Physical AI Data Factory Blueprint into Nebius’ infrastructure to address two core bottlenecks: fragmented tooling/infrastructure and the scarcity of high-quality training data for rare real-world scenarios. The companies listed the platform’s core technologies:

• Compute power: NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs on Nebius AI Cloud
• Orchestration: NVIDIA OSMO for managing the entire development pipeline
• Data generation: NVIDIA Cosmos foundation models to create physics-consistent synthetic data
• Deployment: Includes the Nebius Token Factory for low-latency inference and edge deployment

The platform is available now in U.S. and European data centers.

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Leading physical AI companies build in the cloud

RoboForce builds AI robots for unstructured outdoor environments — solar farms, construction sites, agricultural fields — where encountering edge cases is a daily reality. Using NVIDIA Cosmos open-world foundation models on the Nebius cloud, RoboForce said it cut pipeline setup time by more than 70% and significantly accelerated the time to production for new policies.

“Manual handoffs between data generation, simulation, and training mean our GPUs can sit idle — costing us both time and money,” said Calvin Zhou, co-founder of Milpitas, Calif.-based RoboForce. “Using OSMO agentic orchestration, our engineers can push a single configuration file and run the entire pipeline end to end.”

“We’re generating thousands of scenario variations with NVIDIA Cosmos on Nebius AI Cloud, powering our AI data flywheel and accelerating the development of our robot foundation model,” he added. “This allows us to push hardened robot models straight to the edge and cut our iteration cycles from weeks to days.”

Ann Arbor, Mich.-based Voxel51 provides data visualization, curation, annotation, and analysis capabilities for teams to build high-quality datasets for model training and simulations. By running FiftyOne workflows on Nebius GPU clusters, Voxel51 customers can curate, augment, and quality-check visual datasets at scale—reducing the time between data collection and model deployment.

“Data is the biggest determinant of computer vision success. As vision AI systems become more capable, the limiting factor is no longer algorithmic innovation but the quality, coverage, and observability of the data used to train models,” said Brian Moore, co-founder and CEO of Voxel51. “Nebius gives our users the compute infrastructure for running complex data tasks such as auto-labeling and generating novel scenes at the speed and scale needed by physical AI systems.”

Together with Nebius cloud for physical AI and NVIDIA technologies, Voxel51 is delivering a synthetic data generation pipeline for its customer, Porsche Engineering, to accelerate autonomous driving data-augmentation workflows.

Milestone Systems is a global leader in intelligent video management software and the company behind the Hafnia platform for computer vision. It chose Nebius to fine-tune its next-generation vision-language models (VLMs).

Brøndby, Denmark-based Milestone curates real-world video footage into compliant, annotated training data, then it uses NVIDIA Cosmos Reason to fine-tune it into highly accurate, use-case-specific VLMs. For this computationally intensive work, Nebius provides sustained access to large GPU clusters, high-throughput data pipelines, and managed workflow orchestration that keeps training runs stable and cost-efficient.

“We evaluated several cloud providers, and Nebius offered the best combination of GPU availability, price-performance, and hands-on engineering support for our physical AI and VLM training workloads,” said Edward Mauser, director of Hafnia at Milestone Systems. “We chose Nebius not just for their tech, but also for their commitment to data sovereignty — guaranteeing that European customers’ data can remain within Europe.”