General purpose
intelligence

for every robot
AI skills to perceive, plan, and act in the physical world
Emergence of general intelligence through skills
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General Robotics is building general-purpose intelligence for every robot in any form, across any real-world scenarios. True generalist robots need more than just a foundation model. They must adapt across morphologies, be simple to program, and meet rigorous safety standards.

We believe general intelligence emerges from rich composition of robot skills — not just larger models. By combining modular AI skills, we enable robots to sense, reason, and act with precision. Our approach is data-efficient, interpretable, and built for safety-critical use.

AI skills for every robot

Skill composition via code synthesis

Simulation as a source of feedback

Easy access through cloud

GRID
General Robot Intelligence Development Platform
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Open GRID

For individuals.

Rapid Prototyping.

Directly from the browser.

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GRID Enterprise

Large organizations.

Develop and deploy.

Private infrastructure.

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Open GRID makes robot
intelligence accessible
Rapid access to AI skills for every robot
Every AI Skill
Access diverse AI skills for perception, planning and action in the physical world.
Every Robot
Multiple robots with high fidelity simulations for zero-shot deployment.
Right from the Browser
Web-based sandbox to access, compose and test AI skills from your from the browser without hardware dependencies.
Every AI Skill
Access and compose from a library of perception and action skills.
Every Robot
Multiple robots with high fidelity simulations for zero-shot deployment.
Right from the Browser
Deploy, manage, and monitor your custom models from your own browser with no installation or hardware dependencies.
GRID Enterprise makes
robot intelligence scalable
Scalable, customizable
and private AI skills for every robot
AI Skills
Create, compose and test AI skills with RL, ML, imitation learning and agentic architectures.
Data Collection
Synthetic data collection on cloud at scale, across any form factor and 
use case.
Training & Testing
Integrative and modular testing through sim feedback and deployment processes. Bridge sim-to-real gap with extreme data augmentation.
Integration
Integrate with custom robots, use cases, and tech stack.
Deployment
Deploy AI skills for any form factor, including aerial, wheeled, manipulation, quadruped and/or humanoid on cloud, on edge or both.
AI Skills
Create, compose and test AI skills with RL, ML, imitation learning and agentic architectures.
Data Collection
Synthetic data collection on cloud at scale, across any form factor and 
use case.
Training & Testing
Integrative and modular testing through simulation feedback and deployment processes. Bridge sim-to-real gap with extreme data augmentation.
Integration
Integrate with custom robots, use cases, and tech stack.
Deployment
Deploy AI skills for any form factor, including aerial, wheeled, manipulation, quadruped and/or humanoid on cloud, on edge or both.
Power every robot on the planet with limitless intelligence
We’re scientists, engineers, and builders behind some of the most widely adopted robotics and AI tools — from AirSim and Neural Simulation to open-source projects like ChatGPT for Robotics, ClimaX, and PACT.
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Ashish Kapoor

Co-Founder & CEO

Sai Vemprala

Co-Founder

Dinesh Narayanan

Co-Founder

Shuhang Chen

Co-Founder

Jonathan Huang

Head of AI

Jim Piavis

Director

Noam Schafer

Director of Partnerships

Geordie Moffatt

Head of Simulation

Pranay Reddy

Research Engineer

Sarthak Bhagat

Research Engineer

Pushkal Katara

Research Engineer

Brandon Rishi

Research Engineer

Arthur Lovekin

Research Engineer

Mayank Garg

Software Engineer

Yasvi Patel

Product Manager

David Merrill

Advisor

Foundations in Research
ALL BLOG
Our research is grounded in deep learning and safety. We believe that general-purpose intelligence for robots won’t come from monolithic models, but from modular deep learning structures. Real-world deployment demands systems that are composable — modular, adaptable, and inspectable by design. Safety is not a layer to add later; it’s a foundation. That’s why we build mechanisms for blame assignment and interpretability into the architecture itself, ensuring accountable and reliable behavior from the ground up.
Intelligence for every robot