Solutions
From Physical AI planning to simulation, learning data, robot AI and real machine systems.
What we offer
01
Physical AI Advisory
Organize field problems and design the tasks, technology, equipment and PoC plan.
02
Real-to-Sim & Digital Twin
Reconstruct equipment, robots, objects and environments from CAD, photos, video, dimensions and logs.
03
Physics Simulation & Synthetic Data
Reproduce contact, friction, deformation and flow to generate learning and evaluation data.
04
Robot Learning & AI Development
Build learning environments connecting to imitation learning, RL, VLA and action models.
05
Sim-to-Real Validation
Transfer motions and control conditions learned in simulation to machines, then correct with field data.
06
Robot System Development
Integrate arms, cameras, sensors, end effectors and control AI through to a real PoC.
01. Consulting
Physical AI Consulting
We support you from the stage where the task to automate and the technology needed are still undecided. We organize the field problem, objects, working conditions, required precision and constraints, then design a Physical AI architecture and PoC plan.
- Problem & task definition
- System architecture proposal
- Robot / sensor / AI selection
- PoC plan
- Development roadmap
02. Simulation
Simulation & Learning Data
We turn real equipment, objects and environmental conditions into simulation, generating the data robot AI needs to learn and be evaluated — including failure and hazard conditions hard to reproduce on real machines.
- Simulation environment
- Digital twin
- Synthetic images & video
- Sensor logs
- Success / failure conditions
- Evaluation report
03. Robot systems
Robot System Development
We go beyond simulation — combining robot arms, cameras, sensors, end effectors, action models and control systems through to prototypes, PoC machines and real-machine validation.
- Equipment configuration
- Robot system design
- Prototype / PoC environment
- AI & control models
- Machine validation results
- Improvements for field deployment
Domains
Domains
Manufacturing
Learning and validation before deployment, for grasping, feeding, mixing, conveying and assembling irregular, soft, powder or liquid materials.
Construction & Heavy Machinery
Recognition and manipulation of inconsistent materials such as soil, mud and debris, and robot operation in hazardous environments.
Logistics & Heavy Industry
Handling items with varying shape and hardness — grasping, sorting, loading and picking across many item types and unknown objects.
How we develop
Process
1
Define the problem & target task
2
Review data, equipment & objects
3
Build simulation & learning environment
4
Robot AI & real-machine PoC
5
Field validation & correction