Roboss

Robot learning is bottlenecked by data: real demonstrations are rare, expensive, and hard to scale — they require physical robots, teleoperation rigs, controlled environments, and hours of human labor per usable sample or is bounded to unrealistic synthetic data (think 1990 3d models, or very simple actions). Roboss replaces that process with a pipeline of autonomous agents that manufactures paired (video → action) training data from nothing but text prompts, for any robot morphology. From a behavior description, a synthesis agent generates thousands of photorealistic videos of the target robot or human depending on required data; act by act, feeding each clip's last frame back into the next generation to preserve robot identity, scene consistency, and motion intent — retrying failures on its own and scaling to thousands of behavior variations at near-zero marginal cost. To make sure videos are suitable for training, we leverage physics based verification models, and LLM as a judge to dismiss videos presenting anomalies, hallucinations or any kind of unfeasible action. This data is under the Robotext standard, highest in the industry, with less than 0.1% of unfeasible, uncatched actions. An autonomous annotation agent then labels the footage without human input: a VLM chooses between more than 20 frontier open source labelling and time series tools to enrich the video with posture, heading, movement, and timing frame by frame, enriches every sample with semantic context — the objects in the scene and the actions being performed — proposes action labels with confidence scores, and cross-validates each one for physical plausibility before compiling clean, timestamped action sequences. Accepted and rejected samples are separated automatically, and the result is packaged as a ready-to-use synthetic dataset. A simple prompt of what dataset you need results in the highest quality data delivered in minutes instead of months. Synthetic data is expensive, unrealistic blender models, or primitive world models. We offer a true upgrade in movement complexity, cost, speed and quality of data. This is a true revolution to actual tools, imagine your dataset in 10 minutes instead of months, richer and cheaper. This is what Roboss delivers, in a projected $70B industry.