Data and compute for physical AI

We work with early-stage robotics and physical AI teams across the world, building VLA models, world models, perception systems, and autonomous robot platforms.

A few things set our compute apart:

• One campus, fewer handoffs — data collection, GPU training, and robot validation sit together in our Las Vegas foundry, reducing the data movement that slows physical AI work.
• Built by a robotics company — Richtech designs, builds, and deploys its own commercial and industrial robots, so we build our compute services around workloads we run ourselves.
• From model to validation — beyond training, our facility includes space and hardware to test how models perform on real robots.
• Sized to your stage — engagement models designed for early-stage teams, not only hyperscale buyers.

Our compute is built for the full physical AI model stack — vision-language-action (VLA) models, world models, vision-language models, perception and policy networks, and multimodal sensor-fusion models. Typical workloads include large-scale training, fine-tuning and post-training, reinforcement and imitation learning, synthetic data generation, and digital-twin simulation.

We offer compute as reserved or project-based capacity, sized to your stage. Whether you're generating synthetic data, training a foundation model, or fine-tuning a deployment policy, we'll help you scope the right setup. Pricing depends on configuration and term — reach out for a quote.

Our AI Compute runs on enterprise-grade data center infrastructure and NVIDIA GPU platforms, including GPUs suited to NVIDIA Isaac Sim and Cosmos-class simulation workloads.