Eastworlds
Eastworlds

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We help robots
leave[1] the lab faster.

[1] A robot leaves the lab when it can operate in the real world, solve real problems, and generate real economic value. Over time, it will be able to get what it wants, regardless of whatever obstacles are in the way.

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01

Our 3 Pillars

Pillar 1

1

Build fast

Embodied AI Accelerator

We help teams turn robotics ideas into deployable systems at speed.

The Eastworlds Accelerator concentrates top embodied AI talent from around the world into a single execution hub — bringing researchers, engineers, and founders together to build side by side. By operating as a high-density environment of top minds, we accelerate iteration, knowledge transfer, and breakthrough problem-solving.

Teams are equipped with everything needed to ship: multi-stage funding, access to humanoid and non-humanoid hardware, access to companies for pilot projects and a full software stack including teleoperation, simulation, and tooling.

We also partner with leading research labs globally to solve the hardest technical challenges — from manipulation to perception to control — allowing founders to stay focused on growth, deployment, and real-world implementation.

Our focus is simple: move from prototype to real-world readiness as quickly as possible.

2

Deploy fast

Physical AI BPO

We take robots out of the lab and put them to work.

BPO (Business Process Outsourcing) traditionally meant outsourcing human labor. Physical AI BPO extends this model by deploying robots-as-a-service to perform real-world tasks across industries such as retail, hospitality, and security.

This approach enables immediate deployment without waiting for full autonomy. While VLA-based systems require long training cycles and high reliability thresholds, teleoperated and hybrid systems can be deployed today, generating value from day one.

Over time, the data collected from these deployments enables increasing levels of autonomy. But we win early by securing real commercial contracts, embedding into workflows, and owning the distribution layer from the start.

3

Learn fast

Embodied AI Data Lake

Every deployment generates high-fidelity data from the most valuable environment: the real world.

Unlike controlled lab settings or simulated environments, Eastworlds captures chaotic, unstructured, and edge-case-heavy data from live operations. This includes egocentric teleoperation data, multi-modal sensory inputs, and task execution feedback across diverse environments.

In the near term, this data directly improves system performance — increasing manipulation precision in hands and arms, enhancing stability, and informing rapid hardware iteration.

Over time, this dataset becomes the foundation for training next-generation models, including Vision-Language-Action (VLA) systems and World Action Models (WAMs), enabling a transition from teleoperation to full autonomy.

The result is a compounding data advantage that accelerates both capability and deployment speed.

02

Our Research Partners

Carnegie Mellon University

Carnegie Mellon University
University of Oxford
Shanghai Jiao Tong University
Nanyang Technological University
Carnegie Mellon University
University of Oxford
Shanghai Jiao Tong University
Nanyang Technological University
Carnegie Mellon University
University of Oxford
Shanghai Jiao Tong University
Nanyang Technological University
Carnegie Mellon University
University of Oxford
Shanghai Jiao Tong University
Nanyang Technological University

03

Initial Use Cases

Domestic Helper

Handles deep cleaning and seasonal maintenance, including polishing windows, wiping countertops, removing wall scuffs, and clearing dust and cobwebs from hard-to-reach areas—keeping the home clean and well maintained.

Domestic Helper
Retail
Hospital Support Staff
Security Guard
Waste Collection Workers
Hotel Housekeeping
Mechanic
Plumbing
HVAC Technician
Entertainment

04

Residents

Amanda Y.
Bayley W.
Bryan L.
Chyna Q.
Cix L.
Darius F.
David G.
David H.
Hoa M.
Ismail K.
Jan L.
Jason L.
Javier Y.
Jianfei Y.
Jonathan M.
Kristóf F.
Lesya H.
Michael C.
Perla M.
Raphael H.
Vitaly B.
Xenia B.
Zati H.
  • Amanda Y., COO @ BitRobot
  • Bayley W., Co-founder @ PrismaX
  • Bryan L. @ Virtuals Protocol
  • Chyna Q., Co-founder @ PrismaX
  • Cix L., CEO @ REK
  • Darius F., Project Lead @ ETH Zurich Robotics Club
  • David G., Co-founder @ Midcentury AI
  • David H., Assistant Professor @ Robotics Institute, Carnegie Mellon University
  • Hoa M., Founder @ Feather Robotics
  • Ismail K., Founder @ Oli Robotics
  • Jan L., Founder @ OpenMind
  • Jason L., CEO @ Flyby Robotics
  • Javier Y. @ Eastworlds
  • Jianfei Y., Associate Professor @ Nanyang Technological University
  • Jonathan M., CEO @ Budbreak
  • Kristóf F., VP of Tech @ ETH Zurich Robotics Club
  • Lesya H., Founder @ Spacer Robotics
  • Michael C., Co-founder @ FrodoBots
  • Perla M., Associate Professor @ Oxford Robotics Institute
  • Raphael H., Principal @ Tioga Capital
  • Vitaly B., Co-founder @ Ultimate Fighting Bots
  • Xenia B., Co-founder @ Ultimate Fighting Bots
  • Zati H., Senior Lecturer @ University of Malaya