Kosmo, 3D world data engine, transforms the real world into AI-ready intelligent 3D spaces — understandable, interactive, and trainable — with a single capture: delivering large-scale, high-quality real-world data for robot training, improving the acquisition efficiency of this critically scarce data by 100× 1, and helping robots bridge the gap from simulation to reality.
AI Needs Scalable, High-Quality 3D Data to Move into the Real World
Embodied AI has long faced a data "impossible triangle" — high quality, large scale, and low cost rarely coexist. Internet data lacks spatial information; simulation falls short of the real world; real-robot collection is costly and hard to scale. World models face the same challenge: the more realistic the generation, the more it depends on real-world calibration. High-quality, spatially aligned real-world data is becoming the industry's scarcest strategic resource.
From Data to Training Ground — Kosmo Covers the Full Robot Training Pipeline
Pre-Training
Real-world data at scale. Kosmo generates 3D data at 5× 2 industry speed, delivering three spatially aligned outputs in one capture — 3DGS, mesh, and depth — helping robots build consistent, grounded understanding of the physical world.
Post-Training
Close the Sim-to-Real gap. Kosmo One captures real-world material and color data; Kosmo World converts it into Sim-ready assets via AI-driven 3D semantic segmentation — breaking the trade-off between realism and cost.
Evaluation & Deployment
A reproducible, controllable digital testing ground. Environments are accurately reproducible, with obstacles, layouts, and materials freely configurable — enabling long-tail coverage, scalable automated evaluation, and lower real-world testing costs.
World Models
Every imagination, grounded in reality. Kosmo provides precise camera poses, depth data, and multi-view correspondences as the real-world anchor for world models. From a single 3D space, Kosmo auto-generates tens of thousands of training trajectories — improving data acquisition efficiency by over 100× 1.
