Our global network of players generates diverse, high-quality demonstrations through our physics-grounded simulator – while you focus on building the robots.
Post a task and start receiving demonstrations within 24–48 hours. Our global player network means you can collect thousands of diverse demonstrations in the time it takes to set up a single teleoperation rig.
Data from players across age groups, geographies, body types, and experience levels. Diversity of human demonstrations is a key driver of robot generalization – and you can't get it from a single lab team in one city.
No hardware procurement, no specialized staff, no lab space. Pay per demonstration, not per physical setup. Scale up and down on demand without capital commitments or long-term contracts.
Our engine enforces real-world physical constraints – contact forces, gravity, material properties. Player demonstrations transfer to physical robots with dramatically less sim-to-real gap than scripted or synthetic data.
Every trajectory is validated, quality-scored, and delivered in your format of choice: HDF5, RLDS, or LeRobot. Ready to plug directly into your training pipeline – no cleaning required.
Train your policy, identify gaps, post a targeted task for more data. The whole loop runs in days, not quarters. The labs that iterate fastest will win – and Playroll is built to keep up.
| Capability | Playroll | Physical Teleoperation | Synthetic / Scripted Data |
|---|---|---|---|
| Time to first demo | Hours | Months | Days |
| Demographic diversity | Very high | Very low | None |
| Cost per 1k demos | Low | Very high | Low |
| Physical realism | High | Very high | Medium |
| Scales on demand | Yes | No | Partial |
| Human behavior variety | Very high | Low | None |
| Hardware required | None | Extensive | None |
| Ethical data sourcing | Paid fairly | Small team | N/A |
How does simulation data translate to physical robots?
Our simulator enforces real-world physical constraints – which means human strategies for manipulation (grasping, balancing, stacking) translate to physical policies. Sim-to-real transfer isn't perfect, but diverse human demonstrations in a physics-accurate environment dramatically outperform scripted or synthetic data for generalization tasks.
What types of tasks can I post?
Manipulation tasks are our initial focus: pick-and-place, sorting, assembly, tool use, pouring, folding. We're expanding to navigation and multi-arm scenarios. If you have a specific use case, reach out – we're actively building new environment templates with early design partners.
What data format will I receive?
We support HDF5, RLDS (used by Open X-Embodiment), and the LeRobot dataset format. Each trajectory includes joint positions, end-effector poses, object states, actions, and timestamps. Custom fields can be added per task spec.
How is quality controlled?
Every trajectory goes through automated validation: physical plausibility checks, task completion verification, and outlier detection. We also use cross-player consistency scoring. Players build reputations – high-quality contributors get first access to high-value tasks, creating a self-reinforcing quality flywheel.
Are players paid fairly?
Yes – and this is core to our model. Players earn $8–$20/hr based on skill level and task difficulty. We believe the people contributing to AI development deserve to benefit from it. A fairly-paid, engaged workforce also produces dramatically better data than reluctant, underpaid contributors.
When are you launching?
We're in private beta with a small number of robotics labs. Join the waitlist to get early access and potentially shape the platform as a design partner.
Join the waitlist and we'll reach out about early access for labs.