Building the data layer for embodied automation.
RoboWorkData constructs the collection and annotation infrastructure required to feed Vision-Language-Action models and humanoid control policies.
Studio Development Stage
RoboWorkData is building an international collection and annotation infrastructure for structured human task demonstrations.
We are in our early operational phase. We cooperate with robotics partners, research institutions, and logistics groups to validate our collection protocols and build foundational catalogs before deploying contributor networks across wider regions.
Foundational Pillars
How we approach data collection.
Our values guide how we work with contributors, design mockups, and deliver metadata.
Our Mission
To construct the trusted data infrastructure layer that enables Physical AI systems to learn from real human demonstrations—collected, annotated, and cleared with complete transparency.
Why Controlled Mockups First
Mock apartments, logistics zones, and cleaning stations let us control variables, isolate kinetic primitives, and guarantee bystander privacy. It is a deliberate engineering constraint to ensure dataset validity.
Why Consent & QA Matter
Data that cannot be defended legally or technically is a major liability. Versioned digital consent logs and human QA verification checklist logs ensure B2B partners train on safe, licensable assets.
Long-term Platform Vision
We start with service work—cleaning, tidying, mock apartment actions, and light logistics—to validate our annotations workflow. We aim to support broader physical task families for humanoid and service systems globally.
Building or researching Physical AI?
We collaborate with developers, annotation networks, and mock space providers to build standardized data solutions.