The Operating System for
Physical Intelligence
WendyOS brings the mobile development experience to robotics and edge AI. Plug in, code, and deploy to NVIDIA Jetson and Raspberry Pi without the friction.
➜ ~ wendy discover
✔︎ Discovering all Wendy devices [0.5s]
✔ Success
Found 1 Wendy device
Humble Pepper (version: 2025.12.17)
USB 3.2: VID: 0x1D6B, PID: 0x0104
Ethernet: en30, 2.5 Gbps
LAN: wendyos-humble-pepper.local
➜ ~ wendy run
✔︎ Searching for WendyOS devices [0.2s]
✔︎ Builder ready [0.1s]
✔︎ Container built and uploaded successfully! [2.3s]
✔︎ App ready to start [0.1s]
✔ Success
Started app
USB-C Development
No WiFi? No Problem.
Just plug in your device via USB-C. WendyOS handles the networking, letting you deploy and debug as if the device was running locally on your machine.
Modern Toolchain
Swift, Python, Rust & C++
Write in your favorite language. WendyOS treats Swift as a first-class citizen for safety and performance, while fully supporting Python, Rust, and C++ containers.
Remote Access
Debug from Anywhere
Access logs, remote shells, and process status from anywhere in the world. Perfect for managing fleets of robots or distributed sensor networks.
OTA Updates
Fleet Management Built-in
Push application updates or full OS upgrades to one device or ten thousand. Atomic updates ensure your devices never get bricked.
Hardware Accelerated
NVIDIA Jetson & Raspberry Pi
Optimized for the latest edge hardware. Access GPU acceleration, NPU inference, and hardware encoding out of the box with pre-configured permissions.
Physical AI Ready
Sensors & Actuators
Built for the physical world. Simple APIs for GPIO, I2C, SPI, and Camera access make controlling motors and reading sensors straightforward.
A modern IDE for
embedded development
Stop wrestling with SSH keys, cross-compilation toolchains, and flaky connections. The Wendy VSCode extension treats your remote device like a local simulator. Available on the VS Code Marketplace and Open VSX Registry (for Cursor, Windsurf, etc).
One-Click Deploy
Build and push containers instantly.
Remote Debugging
Full LLDB & Python debugging support.
Polyglot
Swift, Python, Rust, C++, TypeScript.
Hardware Discovery
Auto-detect devices via USB or LAN.
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from ultralytics import YOLO
# Load model onto GPU
model = YOLO("yolov8n.pt")
# Start inference stream
results = model.predict(source=0, stream=True)
for r in results:
process_frame(r.orig_img)
✔︎ Container built and uploaded successfully!
ℹ︎ Debugger attached on port 5678
Loaded YOLOv8n model...
Inference running at 30 FPS
Built for the best
AI Hardware
WendyOS is optimized for devices with unified memory architectures, enabling zero-copy data sharing between CPU and GPU for blazing fast inference.
NVIDIA Jetson
Orin Nano, AGX Orin, Thor
- Unified Memory Architecture
- MLX & PyTorch CUDA Support
- Hardware Video Encoding
- 275-2000 TOPS AI Performance
Raspberry Pi
Pi 5, Pi 4 (Experimental)
- Low Power Consumption
- Broad GPIO Ecosystem
- Hardware PWM & SPI
- Affordable Entry Point
Ready to Build Your Next Physical Intelligence Startup?
Whether you are upgrading from Orin or starting fresh on Thor, our engineers are ready to help you ship your next physical intelligence app.