PrismaX
Decentralized data marketplace for physical AI models.
| Date | Investors | Amount | Round |
|---|---|---|---|
* | $11.0m | Seed | |
| Total Funding | 000k | ||
PrismaX is a robotics intelligence platform that provides decentralized data collection and foundational models for physical artificial intelligence. The company was founded in 2025 by CEO Bayley Wang, who has a background in robotics at MIT, and COO Chyna Qu, who co-founded the DeFi protocol DeFiner. They established PrismaX to build and scale foundational models for physical generative AI, addressing the industry's need for high-quality, affordable data.
The company launched in June 2025, coinciding with a16z's CSX Demo Day, after securing an $11 million seed funding round. The round was led by a16z CSX with participation from Stanford Blockchain Builder Fund, Symbolic, Volt Capital, and Virtuals Protocol. The business model is centered on creating a 'data flywheel', a self-reinforcing cycle where token incentives attract a community of contributors to provide real-world visual data via teleoperation. This data is used to train and improve foundational AI models, which in turn enhances the efficiency of teleoperation, attracting robotics companies who pay for access to the data and platform.
PrismaX's platform is built on three pillars: Data, Teleoperation, and Models. It provides protocols to validate and incentivize large-scale visual data collection, a uniform standard for teleoperation with access to operators and software, and collaboration with AI teams to build increasingly autonomous models. The platform uses technologies like ROS/ROS2, gRPC, and WebRTC for low-latency control and high-quality data streaming. This approach aims to solve the data bottleneck in the robotics industry by creating a diverse, scalable, and less biased dataset compared to centralized methods. The revenue generated from robotics firms using the platform is then used to reward the data contributors, creating a tokenized coordination economy.
Keywords: physical AI, robotics intelligence, decentralized data, foundational models, teleoperation, generative AI, robotics data, machine learning, data flywheel, blockchain incentives, visual datasets, autonomous robots, AI training data, decentralized physical infrastructure, DePIN, data collection, community-driven data, robotics software, AI models, remote robotics