@ZenO4AI

ZenO is building a physical AI data network that captures real-world egocentric human motion data for training robotics and embodied AI models.

The project is live on Base mainnet with an active product allowing users to contribute data via smartphone (ZenO Core app) or browser-based robot teleoperation, earning XP and Prism rewards.

With ~40k followers, a 1.5-year-old account, and working infrastructure that processes IMU data into 6DoF trajectories, this represents a legitimate early-stage AI infrastructure play addressing a real bottleneck in robotics training data.

Green flags: Working product live on Base mainnet with active user missions and data uploads · Clear technical differentiation: converts smartphone IMU data into robot-trainable 3D trajectories · Small but engaged following (~40k) with real product activity and weekly missions · Concrete infrastructure: dedicated iOS app, browser teleoperation, XP/Prism reward system · Addresses genuine AI/robotics bottleneck (real-world manipulation data vs simulation-only training)

Red flags: No explicit token mentioned despite onchain integration on Base · Reward mechanics (XP, Prism, Keys) lack clarity on tokenomics or long-term value capture · Team anonymity - no founder/team info visible in public materials