For shoppers who love buying clothes online but often deal with returns because they couldn’t try them on first, Google’s new experimental app in the U.S. might offer a fresh solution. Called Doppl, this virtual fitting-room tool uses generative AI technology to let users create their own digital avatars to try on any clothing—even generating dynamic try-on videos—aiming to realistically reproduce the look of the garment and narrow the gap between “seller photos” and “buyer photos.”

Create Your Own Virtual Model Using a Photo

The first step in using Doppl is to upload a full-body photo of yourself, clearly visible from head to toe. It's best to wear form-fitting clothing to help the AI model your body accurately. If users don’t have a suitable photo, they can choose from built-in AI-generated model avatars within Doppl.

Next, users can upload images of the clothing they want to try on. For a more realistic result, it’s recommended to choose well-lit photos of clothing with minimal wrinkles. If using images of models wearing the clothes, front-facing photos with arms relaxed at the sides work best, allowing the AI to analyze the garment’s cut and drape.

AI-Generated Dynamic Try-On Effects in Real Time

Unlike traditional online shopping tools that only show flat images of clothes swapped onto photos, Doppl uses generative AI to automatically produce a virtual try-on once you upload your photo. It supports turning static images into dynamic videos. For example, if you see a fashion influencer on social media wearing a floral dress, you can simply take a screenshot and upload it to Doppl. Within seconds, you’ll get a video of yourself wearing that dress, showing details like how the skirt sways as you walk or turn.

This feature isn’t limited to clothes sold on mainstream e-commerce platforms. It breaks the barrier of “only trying on items listed online.” Shoppers can take photos of clothes they find in secondhand shops or vintage stores and instantly see how the item pairs with jeans or shoes they already own. Doppl even lets users adjust details in the virtual try-on, like button placement or sleeve length.

Personal Wardrobe Management and Smart Outfit Suggestions

Doppl isn’t just a try-on tool—it also includes a “digital wardrobe” feature that automatically saves your try-on history and organizes it by style categories such as workwear, casual, or party. The AI also offers outfit recommendations based on season or occasion. For instance, it might suggest: “This trench coat pairs 85% well with your camel-colored scarf,” helping users plan their outfits more thoughtfully and avoid redundant purchases or poor combinations.

Helping Brands Optimize Designs with User Data

For brands, Doppl can also collect behavioral data from users during the try-on process—like dragging a sleeve to change its length or preferring cinched or high-waisted designs. By analyzing these preference trends, brands can optimize their product designs more effectively. For example, a fast-fashion brand might find that Doppl’s data shows high-waisted jeans receive 40% more try-on clicks than average, leading them to adjust production ratios to better meet market demand.

Still in Early Testing

It’s important to note that Doppl is currently an experimental project from Google Labs and is only available for download and testing on iOS and Android in the U.S. Google acknowledges that the AI’s simulated fit and detail rendering still need improvement. There’s no announcement yet about whether an international version will launch or when it might become available in other regions.

Part of Google’s AI Shopping Strategy

Doppl represents another step in Google’s ongoing push to enhance shopping experiences with AI. Previously, Google Search introduced an “AI Mode” feature allowing users to set target prices for desired products. The AI monitors prices across the web and alerts users when a deal matches their target, even helping them auto-complete purchases. These features reflect Google’s broader vision to simplify and improve the online shopping process using AI technology.

Overall, Doppl not only offers consumers the convenience of seeing how clothes will look on them without leaving home, but it also provides brands with unprecedented insight into user preferences, holding the potential to reshape the online shopping experience and supply-chain design processes.