Industry solutions

Physical AI, from prototype to production

Train world models and deploy fleet-scale inference with Crusoe Cloud.

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The support has been first class. We could actually talk to human beings at Crusoe. Crusoe gives us dedicated GPU capacity with the economics of a reservation and the responsiveness of a startup.

Sachin Agarwal
ML Infrastructure & Security Engineering Lead
Roboflow

Why Crusoe for physical AI?

Get the capacity, flexibility, and support you need to build intelligent machines for the physical world.

Scale on demand

Deploy near your fleet or train at gigawatt scale. Get the compute capacity you need, when you need it, without waiting years for it.

Move at your
own pace

Bring your own stack or partner with our solutions team to optimize your physical AI workload pipeline.

Build with experts

Partner with our team and bring the next 
big idea to life. Gain early access to NVIDIA accelerated computing through our collaboration.

Where Crusoe supports physical AI

Model labs

Humanoid robotics

Autonomous vehicles

Industrial

Logistics

Internet of Robotic Things (IoRT)

Medical

Crusoe Cloud for physical AI

Build and process datasets
Set up your pipeline to process real world data or generate synthetic data for physical AI scenarios.
CPUs / Simulation GPUs
High-performance data processing
Object storage  / File storage
High throughput storage for real and synthetic data
Direct Connect
Streamline data transfer to Crusoe with zero egress fees
Pre and post training
Train, fine-tune, and evaluate LLMs, Vision-Language-Action (VLA) models, or World Models.
Crusoe Managed Kubernetes / Crusoe Managed Slurm
Orchestrate training and simulation jobs
GPUs
Train models, generate synthetic data, and run simulations
NVIDIA InfiniBand RoCE
Low-latency, high bandwidth fabric for distributed training
VPC
Secure fleet-to-cloud isolation
Container registry
Rapid image pull and workload scaling
Crusoe Serverless Fine-Tuning
Fine-tune LLMs on custom datasets
Deploy for inference
Serve inference with flexible deployment options and superior performance.
Crusoe Managed Inference
Serve inference in the cloud and at the edge
Serverless inference
Deploy via simple API integration
Self-serve deployments
Optimize for latency or throughput, predictable cost
Tailored deployments
Bespoke optimization and an SLA-backed dedicated endpoint
Load balancers
Distribute inference traffic across backends
Crusoe Edge Zones + Crusoe Spark™
Predictable capacity expansion
Low-latency GPU fleet access
Sovereign deployment
"Crusoe provides the latest NVIDIA hardware, extraordinary support, and overall great partnership to enable our data, training, and inference infrastructure. Crusoe is consistently accommodating to our needs and is not afraid to dive deep in helping us solve hard problems."
Philip Petrakian
Technical staff
"We've had good success with Crusoe: the network fabric is very performant, and we're able to pump a lot of gigabits on a constant basis."
Sachin Agarwal
ML Infrastructure & Security Engineering Lead at Roboflow
"It was the speed of back-and-forth between us and the Crusoe engineering team, which happened on Slack. The engineering team was available 24/7. And the cluster was pretty much ready. We didn't have to do any performance optimizations. The GPUs were running at top speed without any additional fixes. It was fairly seamless."
David Novotný
co-founder and CTO of SpAItial AI
Recognition and ecosystem
Industry recognition
Crusoe cloud is a validated NVIDIA Exemplar Cloud.
Partner solutions
Crusoe partners with leading open frameworks like PyTorch, vLLM, SGLang, and works with key partners to deliver physical AI solutions on Crusoe Cloud. 
Learn more on Github.

Frequently
asked questions

Ready to start building?

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