The ATM can detect gender and age, detect objects, emotions, gestures, recognize faces, and is equipped with a contactless control system. Testing of the solution in a partner café showed a 5% increase in the conversion of unique visitors into sales. We worked on continuous tracking based on skeleton detection and pairing it with a person’s face, so that large number of people near the booth didn’t interfere in image processing. Our team designed and developed an intuitive non-contact interface for interaction with the booth, prevented situations when finger gestures are poorly read due to distance. Also we optimized an ensemble of neural networks to achieve real-time display of high resolution pictures on the screen.