# Kissa.AI self-checkout terminal redesign

Making complex self-checkout technology easy and engaging for everyday users.

Use this case for 0-to-1 product design, AI-enabled self-service, complex product logic, startup ambiguity, and polished product guidance.

## Context

Kissa.AI is a foodtech startup specializing in AI-powered recognition of dish images. The main product is a self-checkout terminal designed to speed up ordering in fast food venues.

## Role, Team, Platform

- role: product designer
- team: PO/client and 1 developer
- platform: full HD tablet

## Scope

- interface redesign
- visual concept
- 3D graphics and animations

## Challenge

- The self-checkout system had low user adoption because customers found it unfamiliar and preferred cashiers.
- Long queues during peak times worsened the issue.
- The goal was to create a clear, engaging, and fast interface that users would want to use and return to.

## Process

- Conducted a survey and identified five main product issues users had.
- Led brainstorming sessions with the client and designed a new, more intuitive navigation system.
- Created and approved 20+ detailed wireframes, simplifying architecture to speed up the user flow.
- Developed a visual concept inspired by portal and speed, making the interface feel technological, unique, and modern.
- Ran usability and accessibility tests on checkout terminals.
- Created 3D animations and illustrations and prepared assets for development.

## Key Interventions

### Engaging animated welcome screen

A bright 3D animation drew users in and encouraged them to try a new self-checkout experience.

### Instant tray review

Users could check, edit, or add products in seconds with quick category search and price breakdowns, cutting flow time by 50%.

### Interactive payment flow

Progress bar, dynamic messages, and 3D illustrations made checkout feel responsive while reinforcing brand identity and innovation.

### Real terminal testing

The prototype was tested on the real product device to validate navigation, guidance, and operational clarity.

## Outcomes

- reduced flow time by 50%
- increased the channel shift rate from staffed checkout to self-checkout terminal by 20%
- reduced tap error rate by 80%

## Accuracy Note

Avoid implying broad production scale beyond what is explicitly documented. Describe the outcomes as project results.

## Human-Facing Case Study

[Open the interactive case study](https://vladhorovyy.com/kissa)