Meet Nuvi: the AI desk companion that goes from Q to cute
Making retail smarter: build context-aware experiences with the Arduino® VENTUNO™ Q board
You step into a fitting room carrying two jackets and a pair of trousers. You like each piece, but you are not sure they work together – and which jacket is better. Normally, you would take a photo, message a friend, or walk back outside to ask a store assistant. But imagine if you could simply look into the mirror and tap “Scan your look” instead.
A few seconds later, the mirror recognizes what you are wearing, identifies colors, and suggests how you might complete the outfit. Perhaps with a shirt or an accessory – available in the store – that will tie everything together.
This is the experience behind the Smart Mirror example running on VENTUNO Q . It begins as a personalized style advisor, but it also points towards a new kind of retail experience: one in which physical spaces can understand what customers are doing and offer relevant guidance in real-time .
We recently published a full tutorial on Arduino Docs that you can follow to build your own Smart Mirror with the board. While straightforward to replicate, we think this use case is very interesting both from a technological and an experiential standpoint. Let’s dive in.
The Smart Mirror application uses a USB camera to provide a live video feed. When you tap “Scan your look”, the latest camera frame is analyzed locally on VENTUNO Q by the Qwen3-VL Model, accessed through the Arduino VLM Brick.
The model is built to analyze the image, identify the most prominent garment and its color, and return two short sentences: a description of the outfit and a related styling suggestion. The result is then displayed directly over the live camera view.