One Robot
World models for VLA evals and training.
Winter 2026ActiveIndustrialsManufacturing and RoboticsHard TechMachine LearningRoboticsAISan Francisco, CA, USA
Company
https://www.onerobot.ioOne Robot builds simulation environments that are realistic to see and realistic to interact with, so robotics teams can train and evaluate robot policies without being bottlenecked by robot time.
Today, improving a VLA often means more real-world hours: setting up the scene, running trials, resetting, and repeating. This loop is slow, expensive, and hard to scale. For example, material handling and manufacturing assembly tasks, models need far more training and evaluation data than teams can collect in the real world.
We use task-specific data to build world model-based simulation environments for hard manipulation tasks (for example, textiles and box folding). These environments help teams run more training and evals, find failure modes faster, and accelerate iteration on action policies with less dependence on real-world data collection and robot availability.
Verdict
High Signal
Market Opportunity
Robotics simulation infrastructure for VLA training targets a rapidly expanding market as humanoid and industrial manipulation companies (Figure, Physical Intelligence, Apptronik, etc.) scale training pipelines. The ICP is clear: robotics teams building action models for manipulators bottlenecked by real-world data collection. Manufacturing automation alone is a multi-billion dollar market and simulation tooling is becoming a critical infrastructure layer.
High Signal
Founder Signal
Hemanth Sarabu: Head of AI at Industrial Next (YC W22) where he led the pivot to end-to-end robot learning, prior roles at Symbio Robotics (deployed at Ford/Nissan/Toyota), Google, and NASA JPL Graduate Fellowship. Also bootstrapped Crescer AI to profitability — a real exit signal. Elton Shon: employee #2 at Industrial Next as Head of Software Engineering, and 4.5 years at Tesla including early work on Dojo and Autopilot. Both founders worked together at Industrial Next and bring deep, directly relevant robotics ML and systems experience.
Medium Signal
Competition
Competitors include Isaac Sim (NVIDIA), MuJoCo/PyBullet for physics simulation, and newer generative sim startups like Archetype AI and potentially Physical Intelligence's internal tools. One Robot's differentiation is task-specific world models trained on customer data rather than generic physics engines, which is meaningful for contact-rich and deformable object tasks. However no competitor data was returned in research, and this space is heating up fast with well-funded incumbents.
High Signal
Product
Live interactive demo at /viz/index.html showing 60-second autoregressive world model rollout with camera visualization. Detailed features: realistic simulation, physics learning, policy testing, synthetic data generation, contact-rich manipulation and deformable objects. Launch video on website. No pricing page, no named customer logos, no API docs.
OverallA Tier
Two deeply technical co-founders with overlapping pedigree from Industrial Next (YC W22). The live interactive demo showing a 60-second autoregressive world model rollout is a rare concrete product signal for a robotics AI company. Detailed features cover simulation, physics learning, and contact-rich manipulation. Main risk is competition from well-funded robotics simulation players and the challenge of commercializing world models. The live demo is a strong differentiator.
Active Founders
One Robot
TierA Tier
BatchWinter 2026
Team Size2
StatusActive
LocationSan Francisco, CA, USA
Last Updated2 days ago