Virtual Try-On Technology: The Future of Digital Shopping Experiences

What began as an innovative feature is now becoming standard. As e-commerce evolves, shoppers expect more than static images—they want to see how products might look and feel on them. Virtual try-on technology is answering that need, turning everyday devices into fitting rooms and merging convenience with confidence. In this article, we explore the leading virtual try-on platforms of 2025 and how generative AI is helping take those experiences to the next level.

Where & How to Use Virtual Try-On

Trying virtual products on is surprisingly easy. Whether it's lipstick, glasses, a jacket, or even a sofa, users can preview how something might look on them or in their space with just a few clicks. Often, there's no need to download anything—though some tools are available as apps, most work right in your browser with no setup—just a camera or photo and you're ready.

Virtual try-on (VTO) technology is now used across fashion, beauty, eyewear, furniture, and more. Most tools work using a blend of computer vision, 3D modeling, and augmented reality (AR). Some even leverage AI to refine the fit, adjust to lighting, and tailor the view to individual users.

Leading and Emerging Virtual Try-On Platforms

Here, we’ll take a quick look at a few standout virtual try-on platforms that are leading the space right now, as well as a newly released service that’s quickly turning heads. From reliable AR veterans to fresh AI-powered solutions, each reflects a different angle of how try-on technology is evolving in 2025.

1. DeepAR

   
   

   

   
   

   DeepAR is widely recognized as one of the most robust AR SDKs for retailers. It supports real-time virtual try-ons for glasses, hats, makeup, and apparel with high realism and low latency, even on lower-end devices. The cross-platform SDK (Web, iOS, Android) makes it accessible and efficient for developers.

   Many well-known brands, including Ralph Lauren, have integrated DeepAR to bring AR-powered experiences into their online stores.

   
   

   

   Explore DeepAR

   
   

2. ShopAR

   
   

   

   
   

   ShopAR enables retailers to transform product pages into fully interactive 3D and AR experiences without needing complex development. Its ultra-realistic modeling is especially well-suited for shoes, eyewear, and accessories, and it integrates easily with major e-commerce platforms like Shopify and Magento. A great example is the brand bloobloom, which uses ShopAR to let customers try on directly through their browser or mobile, turning traditional product pages into AR-powered shopping experiences.

   
   

   

   Explore ShopAR

The Try-On Experience: What Users Really Want

Virtual try-on tools are popular because they're easy to use and offer lifelike previews. People enjoy being able to see how things look and fit without needing to download anything or leave their browser. When I tested several virtual try-on tools, I was also enjoying preview outfits directly on my face, felt surprisingly empowering in the potential purchase. On the other hand, the experience wasn’t without its limitations. In some cases, the fabric textures appeared slightly unrealistic, and the interface occasionally lagged on mobile, likely due to rendering demands. Modern platforms are working to overcome these limitations through AI-based realism, lighter processing models, and better adaptation to actual product materials.

Generative AI Joins the Virtual Try-On Movement

The next wave of virtual try-on innovation is being shaped not only by AR, but also by generative AI—offering new ways to visualize apparel using just a single image. Unlike traditional systems that layer garments onto a live camera feed, generative approaches produce full-body try-on results in multiple poses and styles from minimal input. Three platforms helping define this space are Kolors, ZenCtrl, and Google Shopping’s Try It On.

1. Kolors

   
   

   Kolors blends open-source development with tools that support the fashion industry’s growing interest in generative try-on. Alongside features such as “Dynamic 360° View”, it offers a reproducible framework that helps researchers, developers, and creatives visualize clothing in motion and from multiple angles. With a focus on visual consistency and accessibility, Kolors is emerging as a flexible, open model for how AI-powered VTO can evolve in fashion retail.

   
   

   

   Explore Kolors

   
   

   

   HuggingFace Kolors-Virtual-Try-On

   
   

2. ZenCtrl

   
   

   Developed by Fotographer AI, ZenCtrl is a lightweight toolkit designed to generate polished, on-brand visuals from just a single image. Without the need for training or custom datasets, it outputs consistent multi-angle views across various environments and styling contexts. ZenCtrl’s strength lies in its adaptability for marketing, fashion, and storytelling use cases, giving brands a way to scale creative production efficiently.

   
   

   

   Explore ZenCtrl

   
   

   

   HuggingFace ZenCtrl

   
   

3. Google Shopping's Try It On

   
   

   

   
   

   Google Shopping's Try It On uses generative AI to simulate garment fit and drape on real user photos, offering a personalized view of how products may look. Updated in May 2025 with "AI Mode," it adds tailored recommendations and styling options, all accessible through mobile and Google Search. Also as part of Google's broader Shopping Graph, it scales personalized shopping to millions. Currently, the feature is being offered as an experimental rollout in the U.S. through Search Labs.

   
   

   

   Explore Google Shopping Try-On

Conclusion

Virtual try-on tools have become a natural part of the online shopping experience. As both AR-powered and generative AI-driven approaches evolve, the boundary between physical and digital continues to blur—shaping not just how we shop, but how we imagine and interact with fashion itself.

These technologies are not just about convenience; they’re about creating immersive, intuitive, and emotionally engaging experiences that are steadily becoming the norm. And as they improve, so do our expectations for what digital shopping can be.