Computer Vision. Cloud to Edge.

AI models can be designed for different tasks, like recognising things, drawing, processig text and much more. Training is about specializing them. Take an "AI artist model" for instance. Training is about teaching it to draw exactly how you need. Renaissance art? Disney animations? Anime?

Where should your AI model be hosted? Most likely in the cloud. Why? because if you need to process 10 images per day, or 10 million, the setup does not change, it just scales. Models can be swapped or improved without touching your hardware.

Sometimes the AI needs to live inside the device itself. A camera, a sensor, a machine on a factory floor. This is usually required when it needs instant response, or requires the data to "stay in the box". No worries: AI models can be deployed on standalone hardware. We deploy AI models on Hailo, Axelera, and Nvidia accelerators—compact, power-efficient hardware for edge inference.

The AI model is just the brain. But you will often also need hardware (computing units, sensors or actuators), to interact with other digital systems (APIs), interfaces and the rest of the software that wrap around it. We build the whole body, not just the brain.