To address this challenge, Rhoda pretrains its models on internet-scale video — hundreds of millions of clips — to build a foundation in motion, physics and physical interaction, then post-trains the system on smaller sets of robot data to learn embodiment-specific behaviors and translate video predictions into robot actions.

“We believe the next era of robotics requires models that understand how the world moves — not just what it looks like or how it’s described in language,” said Jagdeep Singh, cofounder and CEO of Rhoda.

The resulting system continuously observes its environment, predicts future states as video, converts those predictions into actions, executes them and re-observes the world — repeating this process every few hundred milliseconds in a closed loop.

Rhoda calls this architecture a Direct Video Action (DVA) model that links perception and control by continuously updating robot actions as conditions change, enabling real-time, physics-aware operation. The system’s video-based pretraining allows it to learn new tasks quickly — often with as little as 10 hours of teleoperation data — and forms the foundation of FutureVision, the intelligence layer powering Rhoda systems and future partner platforms. 

Rhoda’s technology has already demonstrated autonomous operation in production environments, where robots must handle continuously changing materials, layouts and workflows. In a recent high-volume manufacturing evaluation, Rhoda completed a component-processing workflow in under two minutes per cycle without human intervention, exceeding customer KPIs.

“In manufacturing, tasks with high variability have historically resisted automation. The real challenge isn’t solving it once, it’s delivering consistent, reliable output under real-world production conditions,” said Jens Wiese, Managing Partner at VC firm Leitmotif and former Volkswagen Group executive. “What impressed us about Rhoda’s approach is its ability to adapt to conditions that typically require human intervention. Technologies like this can dramatically expand the scope of what can be automated, playing a pivotal role in re-industrializing mature economies.”