How does the CAINZ Fitting Room system work?

The system uses generative AI to create realistic interior images with selected products. Customers see the results on in-store screens, aiding purchase decisions.

What challenges arise during implementation?

Key issues include visualization accuracy and algorithm speed. Details and color combinations aren't always rendered correctly, and data processing can take longer than expected.

What benefits does AI bring to retail?

The technology reduces product selection time, lowers return rates, and boosts customer satisfaction. It also allows testing interior combinations without physical furniture placement.

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Artificial intelligence

Japanese Retailer Tests AI for Virtual Interior Fitting in Stores

June 29, 2026

Photo: ITmedia

Quick answer

CAINZ is testing generative AI for in-store interior visualization via the CAINZ Fitting Room system. The goal is to increase sales through convenience, but the technology requires improvements in accuracy and…

Japanese retail chain CAINZ has launched a pilot project integrating generative artificial intelligence into its store floors. The system, called CAINZ Fitting Room, enables customers to visualize how selected items—such as furniture, decor, or finishing materials—would look in an interior setting.

The technology relies on digital screens installed in stores. Users select preferred items from the catalog, and the algorithm generates an image showing their placement in a virtual room. This helps assess item compatibility and alignment with the room's style before purchase.

The project aims to boost sales by simplifying the product selection process. However, developers note that the technology is not yet perfect: challenges include accurately rendering textures, lighting, and proportions. Additionally, processing requests requires significant computational power, impacting system speed.

CAINZ plans to continue testing to optimize algorithms and enhance the user experience. If successful, similar solutions could expand to other home-focused retail chains.

Common questions

How does the CAINZ Fitting Room system work?: The system uses generative AI to create realistic interior images with selected products. Customers see the results on in-store screens, aiding purchase decisions.
What challenges arise during implementation?: Key issues include visualization accuracy and algorithm speed. Details and color combinations aren't always rendered correctly, and data processing can take longer than expected.
What benefits does AI bring to retail?: The technology reduces product selection time, lowers return rates, and boosts customer satisfaction. It also allows testing interior combinations without physical furniture placement.

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