A New Delhi-based startup aims to transform the retail apparel sector by introducing android-based kiosk systems in their physical showrooms. These kiosks facilitate customers in selecting and ordering products not currently in stock at the store. Additionally, they collect customer information for delivery to their specified address upon restocking.
The client required the kiosk to operate in a single application mode, restricting users from accessing any other app apart from the client’s application.
The search function within the app needed an AI feature allowing users to upload images of shirts, t-shirts, or trousers for the system to identify their color, pattern, and style. It should then suggest options matching the user's search criteria.
We tailored the Android OS and integrated a lockdown mechanism to achieve a single application mode. Close collaboration with the client’s kiosk vendor/manufacturer ensured seamless installation of the customized OS on the devices.
As a SaaS-based product, customizing the app’s UI to suit each customer’s style posed a significant challenge. To address this, we developed and integrated a server-driven UI for the entire application, guaranteeing a personalized and cohesive experience for every user.
The tagging engine utilizes a proprietary deep learning framework, which is adaptable for creating tags tailored to various scenarios during image-based searches. This enables the system to assign pertinent tags to products, ensuring a highly refined and individualized user experience.
