Eastworlds
Eastworlds is a neodeployment lab for embodied AI that helps robotics teams bridge the gap between controlled demos and real-world field operation. The company generates structured robot demonstrations with synchronized video, robot state, operator actions, and task metadata for imitation learning. Eastworlds also supports live deployments with teleoperation workflows, operator supervision, and field monitoring to keep the data flywheel turning.
- Artificial Intelligence
- AI Agents
- Robotics
- Software Only
Funding
Founders
Product
Problem
Robotics teams are building increasingly capable machines, but real-world deployment remains the bottleneck. Robots need field exposure to improve, yet getting them into live environments requires an operational layer most teams are not built to run. This creates a deployment catch-22: robots need real-world data to improve, but they must be deployment-ready before they can enter the field, so the data flywheel never starts.
Solution
Eastworlds is a neodeployment lab for embodied AI that combines data infrastructure, operations infrastructure, and real-world robotics lab services. The company helps robotics teams bootstrap the data flywheel by generating high-quality, diverse, in-the-wild training data before broad rollout. Eastworlds supports live deployments with teleoperation workflows, operator supervision, field monitoring, and exception handling. Data collected during deployment is structured and fed back into training pipelines, turning deployment activity into the next training set rather than leaving it trapped in logs and one-off fixes.
Target Audience
Primary customers are robotics teams developing embodied AI systems that need field-ready deployment support and high-quality real-world training data to scale from controlled demos into live operation.
Features
- Structured robot demonstrations with synchronized video, robot state, operator actions, and task metadata for imitation learning
- Custom data generation tailored to specific robot, task, environment, and format requirements
- Teleoperation workflows and operator supervision for live field deployments
- Field monitoring and exception handling infrastructure to manage real-world edge cases
- Continuous loop from deployment back into training data, enabling iterative improvement across pilots