Announcing WorldSight AI: Empowering Global Contributors to Build the Future of Physical AI

We are thrilled to officially unveil WorldSight AI, our global, real-world consumer-facing data collection platform, now live in five markets: Indonesia, Vietnam, Malaysia, Nigeria, and Kenya. This launch marks a definitive step in our mission to build a world-scale supply chain for Physical AI—the critical infrastructure needed to turn human know-how into deployable capabilities for the next generation of robotics.

What is WorldSight AI?

WorldSight AI is the consumer-facing gateway to our comprehensive Physical AI data infrastructure. While it serves as the intuitive mobile interface for contributors to record and upload daily motion tasks, it is the vital entry point into our larger, petabyte-scale backend. This robust infrastructure processes, annotates, and curates high-fidelity motion data, bridging the gap between passive human observation and the active, intelligent systems required for Physical AI.

While AI models have mastered text and static images, Physical AI—the ability for robots to perceive, reason, and act in the real world—remains the true frontier. To achieve this, robots need to learn from the nuance of human motion and physical interaction. WorldSight AI empowers everyday smartphone users to become contributors, recording high-quality motion capture tasks that help machines learn the complexity and diversity of the physical world.

Examples of Supported Data Scenarios

To ensure our robotics models are firmly grounded in the complexities of unstructured reality, we are developing a foundational matrix of human skills. Our initial group of contributors is actively providing data for the high-priority scenarios, starting with the following:

• Culinary Operations (Cooking)

  • Food Prep: Assembling fresh items like sandwiches or salads.

  • Heat-Based Cooking: Searing steaks, baking, or preparing pasta and sauces on a stove-top.

• Domestic Upkeep (Cleaning)

  • Kitchen & Surface Maintenance: Scrubbing floors, organizing kitchen supplies, and sanitizing stove-tops.

  • Living Area Management: General room tidying, making beds, and sorting laundry.

  • Manual Gardening: Basic yard maintenance and watering plants.

• Technical Repairs & Tool Utilization

  • Mechanical Servicing: Repairing small electronics, motors, or automobiles.

  • Home Fixes & Assembly: Installing household infrastructure like plumbing, or assembling furniture and devices.

  • Specialized Landscaping: Utilizing power tools or equipment for advanced garden upkeep.

Building a Global Supply Chain

This launch is a milestone in our strategy to build a world-scale supply chain for embodied data. By combining institutional partnerships with a global, decentralized expert network, we are capturing the high-variance, real-world scenarios—including rare failures and recovery cases—that are crucial for making robotics models robust and generalizable. 

Responsible Innovation: Our Compliance Framework & Economic Layer

The future of AI shouldn't just be scalable—it must be equitable and compliant. We have integrated a proactive global compliance framework and a novel economic layer directly into our foundational structure to ensure the highest standards of ethics and data integrity.

• Compliance by Design: Navigating the complex landscape of Physical AI data requires rigorous governance. Our architecture is GDPR-native and addresses the critical challenges of privacy, data sovereignty, and cross-border data transfer mandates. We are committed to responsible data use, ensuring that every piece of information collected is handled with the highest standards of transparency, security, and ethics.

• An Economic Layer for Contributors: We recognize that our contributors are generating high-fidelity, tacit knowledge that is indispensable for embodied AI. Our economic layer ensures that every contributor is fairly compensated for their effort and data. By utilizing transparent valuation tools, we guarantee that the people who help teach the next generation of robots can participate directly in the value they help create.

What’s Next

We are just getting started. We have an aggressive roadmap for rapid expansion and are currently preparing to announce the next 10 countries joining our network next month.

To our new contributors in Indonesia, Vietnam, Malaysia, Nigeria, and Kenya: welcome to the future of Physical AI. By participating, you are helping turn human know-how into deployable, scalable capabilities for the next generation of robotics.

About Anaxi Labs

Founded in 2024 by Carnegie Mellon University alumni in Computer Science and Robotics, Anaxi Labs is building a world-scale AI data supply chain and a programmable marketplace for AI components. As industry partner of top academic institutions such as Carnegie Mellon University, we work with leading minds in AI data, cryptography, and robotics research, with a team that brings experience building and operating household-name products used by hundreds of millions of people and hands-on depth managing petabyte-scale datasets through real model-training pipelines.

Our mission is to transform human know-how into deployable, scalable capabilities for the next generation of Physical AI. Together, we are committed to transforming the future of humanity by unlocking the power of what science can do for people, society, and the planet.

Interested in joining the network or learning more about our data infrastructure?

Visit https://www.worldsight.ai/ to get started or learn about the company at https://www.anaxilabs.com/.