Axis Robotics
Category: AI Infrastructure
Axis Robotics is building a distributed, crowdsourced data infrastructure for Physical AI, enabling anyone with a web browser to generate robot training data through browser-based simulation. Axis Robotics was founded in 2025. The company is led by Chris Feng. Based in Berkeley, California, United States. Team size: 11-50. Total funding raised: $12M. Latest round: Seed. Key investors include Hack VC, Nomad Capital, Pi Network, 10K Ventures.
- Founded
- 2025
- Headquarters
- Berkeley, California, United States
- Team size
- 11-50
- Total funding
- $12M
Value proposition
Axis Robotics solves the robot training data bottleneck by enabling anyone with a web browser to generate diverse, high-quality training data through browser-based simulation — replacing expensive teleoperation setups ($40K+/robot) with a distributed community model that produced 100K trajectories in 5 days from 18,000+ contributors.
Products and solutions
Robot Training Data Infrastructure (browser-based simulation platform), MetaSim (cross-simulator meta-simulation layer), Task Generation Engine (12 major task categories with procedural generation), Compounding Data Engine (data generation, collection, training, and improvement on a single platform), Sim Dataset V1/V2, DAgger Dataset
Unique value
Only platform combining browser-based simulation, community-driven data collection, and proven sim-to-real transfer — community-contributed data has been used to train policies deployed on physical robots performing autonomous tasks. Crypto-powered incentive layer on Base blockchain for verifiable, ownership-ready datasets.
Target customer
Robot manufacturers, Physical AI companies, robotics research labs, industrial automation firms, and autonomous vehicle companies needing diverse robot training data at scale
Industries served
Robotics, Physical AI, Industrial Automation, Autonomous Systems, Manufacturing
Technology advantage
MetaSim cross-simulator abstraction layer (MuJoCo WASM-based); Task Generation Engine with 12 major categories and infinite procedural variation; Browser-based data collection (zero hardware requirement); Proven sim-to-real transfer (Little Prince's Rose campaign); Crypto-governed contributor network with on-chain verification; Sim Dataset V1 improved LIBERO-Plus benchmark success rate by 12.9 percentage points over Pi0.5 baseline
How they differentiate
Unlike centralized lab-based teleoperation (Scale AI, XDOF) which requires expensive hardware and dedicated operators, Axis uses a distributed browser-based model where anyone can contribute. This enables 10x-100x more task diversity at a fraction of the cost. The crypto-native incentive layer on Base blockchain also differentiates it from traditional data infrastructure companies.
Main competitors
Scale AI (Physical AI data annotation), XDOF (robot training data pipelines), Physical Intelligence (π) (in-house robot foundation model training)
Key partnerships
Booster Robotics, ManiCore Tech, Pigeon Robotics, Dexmal, Lotus (Lotus Robotics), Geely Auto, Zeroth, Manycore Technology
Notable customers
Booster Robotics, ManiCore Tech, Pigeon Robotics, Dexmal, Lotus, Geely Auto
Major milestones
July 2026: Raised $12M seed round led by Hack VC, Feb 2026: 18,000 community users generated ~100K trajectories across 27 task types in 5 days (beta test), March 2026: Main product launched on Base blockchain, Sim Dataset V1 improved LIBERO-Plus benchmark by 12.9 percentage points over Pi0.5 baseline, 100,000+ global contributors, 1,200+ hours simulation data and 20,000+ hours real-world data collected monthly
Growth metrics
100,000+ global contributors; 452.8 PFLOPS total hash power connected; 19,280.2 on-chain agents; 8,902 active nodes; 1,200+ hours simulation data/month; 20,000+ hours real-world data/month
Market positioning
Early-stage leader in the emerging Physical AI data infrastructure layer, positioned as the "crowdsourced data engine for Physical AI" — competing with centralized data collection approaches by leveraging distributed human participation and blockchain-based incentives.
Geographic focus
Global (headquarters in Berkeley, CA with global contributor network; partnerships with Chinese robotics companies like Booster Robotics, Geely Auto)
About Chris Feng
Ex-COO of Chainbase (blockchain data network); Senior Associate prior; B.S. in Computer Software Engineering from The Ohio State University (Fisher College of Business, Finance & Risk Management)
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Official website: https://axisrobotics.ai/