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Edge Computing

Pi-Autonomous

Robots and autonomous machines. VLM embedded directly on hardware, with or without connectivity.

Who is it for?

Inspection drones

Autonomous infrastructure inspection, in-flight anomaly detection, GPS-free navigation.

Material handling robots

AGVs and logistics robots with visual perception, navigation in dynamic environments.

Quality control

Defect detection on production lines, automatic marking reading.

Capabilities

VLM models optimized for real-time inference on constrained hardware.

Real-time inference

Sub-100ms latency for decision-making in real conditions. Live video processing.

Offline operation

No cloud dependency. The model runs locally, even without connectivity.

Compact models

Optimized for Jetson, Rockchip, or other edge hardware. From 500M to 2B parameters.

Multiplatform SDK

C++, Python, ROS2 integration. Compatible with standard robotics frameworks.

Supported hardware

NVIDIA Jetson

Orin, Xavier, Nano

Rockchip

RK3588, RK3568

Intel

Neural Compute Stick

Qualcomm

Snapdragon X Elite

An embedded AI project?

Let's discuss your use case and integration with your hardware.

Contact us