Intelligence forthe PhysicalWorld
We build systems that enable machines to perceive, reason, and act in the real world with human-like adaptability — bridging digital intelligence and physical execution.
Research Focus Areas
Our Approach
Three Pillars of Physical AI
We are building generalizable intelligence for the physical world — a system that can learn, adapt, and execute across a wide range of real-world tasks.
Perception
Understanding the World
We fuse data from multiple modalities — vision (RGB, depth), force and tactile sensors, proprioception, and environmental context — to build a rich, real-time understanding of complex and changing environments.
- Multi-modal sensor fusion
- Real-time scene understanding
- 3D spatial reasoning
- Adaptive calibration
Reasoning
Decision-Making Engine
We develop foundation models for physical tasks that interpret goals and constraints, plan sequences of actions, and adapt dynamically when conditions change — moving beyond static programming to learning-based decision-making.
- Goal interpretation
- Action sequence planning
- Dynamic adaptation
- Cross-task generalization
Action
Execution in the Real World
Our systems close the loop between intelligence and execution — translating decisions into precise motor actions, continuously adjusting using feedback, and improving performance over time through learning.
- Precise motor control
- Real-time feedback loops
- Continuous improvement
- Sense-decide-act-learn cycle
Core Technology
What makes our approach different
Four technology pillars that enable generalizable intelligence for the physical world.
General-Purpose Robot Brain
Instead of building task-specific solutions, we are developing a unified intelligence layer that can be deployed across multiple hardware platforms and use cases.
Simulation-to-Real Transfer
We leverage high-fidelity simulation environments to train models at scale, reduce real-world data requirements, and safely test edge cases — dramatically accelerating deployment and iteration.
Learning from Demonstration
Our systems learn directly from human actions — reducing the need for manual programming, enabling rapid onboarding of new tasks, and making automation accessible to non-experts.
Hardware-Agnostic Platform
We integrate with existing robots, drones, and industrial systems, acting as a software intelligence layer rather than requiring proprietary hardware.
Applications
Unlocking automation in environments previously considered too complex
Logistics & Warehousing
Autonomous picking, sorting, and packing. Handling irregular objects and dynamic layouts without manual reprogramming.
Manufacturing
Adaptive assembly and inspection with real-time quality control. Systems that adjust to variations in parts and processes on the fly.
Agriculture
Precision harvesting and crop monitoring. Autonomous operation in variable outdoor conditions that defeat traditional automation.
Mobility & Drones
Autonomous navigation in dynamic environments. Inspection, delivery, and monitoring systems that operate without GPS or pre-mapped routes.
Service Robotics
Cleaning, maintenance, and assistance in homes and hospitals. Healthcare support and elder care systems that adapt to human needs.
Construction
Autonomous site monitoring, material handling, and inspection in unstructured environments where precision and safety are paramount.
Why Now
The inflection point for Physical AI
Several converging trends create a unique opportunity to redefine how work gets done in the physical world.
Foundation models enabling generalization beyond narrow tasks
Improved simulation environments for scalable training
Lower-cost, higher-capability robotics hardware
Labor shortages and rising operational costs across industries
Growing demand for automation in unstructured environments
Vision
A universal interface to the physical world
Just as language models became the default interface for digital systems, Physical AI will become the default interface for interacting with the real world.
Enabling massive productivity gains where one human can leverage the output of a hundred machines.
End-to-end physical workflows that operate autonomously — from perception through execution.
A future where intelligence is seamlessly embedded into every machine and environment.
Market Opportunity
Physical AI sits at the intersection of multiple trillion-dollar markets. We believe the category will evolve like cloud computing and LLMs — where a few foundational platforms power a wide ecosystem of applications.
Building the future of Physical AI together
We are looking for research partners, industry collaborators, and exceptional talent to help build the intelligence layer for the physical world.