Physical AI Infrastructure-as-a-Service

The physical layer for Physical AI.

Real robots, environments, teleoperation, data collection and testing — without building and running it all yourself.

The bottleneck

Your model can scale in compute. Access to the physical world doesn't scale as easily.

01 / 07

Multi-Robot Infrastructure

Access a growing fleet across embodiments — robotic arms, quadrupeds and humanoids. Bring your own hardware, or use infrastructure configured around your programme.

02 / 07

Real-World Data Collection

Managed or customer-operated teleoperation programmes. Environment-, task- and embodiment-specific demonstrations, training and correction data at scale.

03 / 07

Physical AI Twins

Replicate your lab, training environment or workflow as a secure, white-label physical setup — without building another facility from scratch.

04 / 07

Testing & Evaluation

Run trained policies on real hardware across defined tasks and scenarios. Measure performance, find failures, generate correction data.

05 / 07

Physical AI Operations

Operators, robotics engineering, scheduling, facility operations, data workflows and QA — the capacity to run programmes continuously.

06 / 07

Commercial Test-Beds

Validate robotics in live manufacturing, logistics and industrial environments in Lithuania and across the EU — alongside future customers.

07 / 07

EU Data Operations

Secure end-to-end data processing and storage on EU-based infrastructure, built around European data protection and AI governance.

How it works

Start with a requirement. Scale from there.

01Define
Agree the model or policy, target embodiment, environment and evaluation criteria.
02Configure
Robots, cell, sensors and teleoperation are set up around the embodiment.
03Run
Policies roll out and data is collected on real hardware.
04Decide
Rollouts are evaluated; failures become correction data.
05Scale
Extend to more embodiments, tasks, environments and locations.