World Cognition Model Framework
A mind that thinks
like a person —
inside the robot.
Cyberbrain builds the World Cognition Model — the brain framework that lets robots reason the way humans do. We focus on the thinking layer, not motor control, and are the first to prove general-purpose operation end-to-end on real hardware.
What we build
We put a mind that thinks like a person inside the robot body. While the industry advances fine manipulation, we give robots the human capacity to reason — so a firefighting robot reasons like a firefighter, and a service robot reasons like a server.
Through chain-of-thought training, we bring frontier large-model reasoning onto the robot itself. The result is a brain that communicates and acts in open, unscripted environments — instead of being confined to a predefined task list.
Company Intro
See CyberBrain in motion.
A short introduction to the reasoning-driven cortex behind our robotics platform.
Technology
Inside the World Cognition Model.
Our reasoning-first brain framework — the layer that lets an embodied machine understand a scene, decide what to do, and act.
Reasoning-first brain
We train the thinking, not the task. A frontier reasoning model, fine-tuned for the physical world, runs chain-of-thought before it acts — figuring out why and how, not just what.
Generalization, not scripting
Trained once, that reasoning carries to tasks the robot has never seen. One mind grasps, plans, reasons about shape and constraint, and converses — zero-shot, with no task-specific post-training.
Self-recursive learning
Every task the robot performs automatically generates fresh chain-of-thought data that retrains the framework and redeploys it. A closed loop that compounds with every run — a data engine manual-demo pipelines can't match.
Proven on real hardware
First to demonstrate a reasoning-first brain end-to-end on real robots, in unscripted environments. Capability keeps compounding — riding a smarter LLM frontier and ever more real-world experience.
Demos
Real hardware, unscripted tasks.
Every clip runs the World Cognition Model end-to-end, with no task-specific post-training. Swipe, drag the bar, or use the arrows.
Human–Robotic Interaction
Puzzle Solving
Team
A team built to put a mind inside the machine.
Ten people, average age 26, drawn from the world's leading AI and robotics labs — with 30+ papers at top venues including CVPR and RSS.
MIT · Harvard · Oxford · Tsinghua · Columbia · Imperial · Brown · Duke · CMU
Embodied reasoning & robotics
Founding teamLed by a four-time RoboCup Junior World Champion with 20+ national robotics awards and a PhD in Electrical Engineering — building robots since 2008.
Multimodal large models
Perception + languageWorld-leading expertise from Harvard and the MIT Media Lab in the multimodal models that form the perception and language core of the brain.
World models & 4D vision
ResearchHarvard and MIT postdocs — world-leading researchers in world models and 4D perception for embodied AI.
The supporting engineering team covers embedded systems, LLM safety, 3D vision, dexterous manipulation, and multimodal large models.
In the research community
Proud sponsor of the CVPR 2026 Sense of Space workshop.
The raise
We are raising our first round on a SAFE.
We have proven the reasoning brain end-to-end on real hardware. This round funds the next step: scaling the ability libraries, expanding the demonstration platforms, and growing the team behind them.
If you invest in frontier robotics and embodied intelligence, we would like to show you the full picture — the architecture, the roadmap, and the data room.