What It Is
Instead of sending everything to a distant cloud, models run on cameras, sensors, controllers, or gateways and decide in milliseconds. The cloud is still used for training, updates, and reporting.
Key Points
- Lower latency: vital for safety and quality control.
- Lower bandwidth cost: raw video and sensor streams need not be uploaded.
- Privacy: sensitive data can stay on premises.
- Resilience: systems keep working when the network is slow or down.
Why It Matters
Edge devices have limited memory, compute, and power, so models must be compressed, optimized, and tested on real hardware.
How ClearLeaff Applies It
We bring AI to factory floors and remote infrastructure, running inference in under 8 milliseconds on ARM and x86 hardware. We use federated learning, ONNX, and zero-touch over-the-air updates to keep fleets current.