In 2025, shoppers use virtual try-on as they browse—Google’s Try-On in Labs lets you upload a photo to see fit on yourself, and VYBE’s Safari extension offers one-tap try-ons during shopping with ~4× retention. Creators and stores generate looks without shoots—Photo AI turns flat-lay garments into model videos, Doji lets people build an AI likeness to try real clothes, and tools like Higgsfield multi-reference and FASHN_AI Try-On v1.5 improve consistency and speed.
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Popular demos from official product accounts, team members, or affiliated creators.
The next-level & fully refined Multi-Reference is now in Higgsfield. Up to 4 reference images. Perfect character consistency. No more random artifacts. Retweet for a FULL Multi-Reference Playbook in your DMs. Be the first to try it: https://t.co/zvIU0FCZHi
Virtually try-on any clothing on any person with AI! It aims to create high-quality virtual try-on for different poses and body shapes. It's works for everything. From anime to real-life images. Examples and link below: https://t.co/DfGIWAsGlK https://t.co/QNjD3JDomw
Summary from ChatGPT: Overview: DressX is building the world’s largest platform for digital fashion, enabling users to dress avatars and real-world photos with AI-generated or 3D-modeled clothing. Available across platforms like Snapchat, Meta, Roblox, and Horizon Worlds, DressX envisions a future where every person maintains a digital wardrobe, just like their physical one. 🧠 Key Insights: Origin Story: Launched during the pandemic, DressX emerged from the realization that digital presence would require new modes of self-expression, including what we “wear” online. Current Offerings: AI-powered outfit generation for static images. 3D digital clothing for avatars in Roblox, Meta, Snapchat, and others. Fashion partnerships with brands like Diesel and high-profile media events. Creator Tools & Democratization: Gen AI empowers everyday users to design digital fashion—without needing to attend fashion school. DressX enables creativity through prompts and templates, offering both mass-market and high-fashion options. Digital Economy: Items typically sell for $0.30 to $1.50, with some limited editions (like Michelle Obama’s immigration dress) going for up to $10,000. A digital scarcity model is possible and already being tested (e.g. limited edition wearables in Roblox). Vision for the Future: As we move from 2D to 3D environments—via AR glasses, Neuralink, or holodeck-like spaces—DressX sees its role in helping users express identity contextually. Future AI fashion may adapt to surroundings or social settings in real time. 🛠️ Business Model & Funding: DressX is a venture-backed startup with billion-dollar ambition. With 100 million digital outfits distributed, they’re positioned to be a core infrastructure provider for the emerging digital fashion economy. 💡 Quote to Highlight: “DressX is your digital wardrobe.” “We believe every person will have a digital avatar—and that avatar needs to be dressed.” “AI will help fashion morph in real-time based on your context—business, party, gaming.” “We want to democratize fashion. Anyone can now be a designer.”
✨ Every time the video models get better, the try on model on Photo AI also becomes a lot more useful, as a large % of my customers now are e-commerce store And showing clothes in a video is nice for sales! With AI this means stores don't need to do expensive shoots flying a model and entire camera and light crew around the world They can just upload a few photos of their models, then upload the clothes, and describe the setting (like a beach in Thailand) and in less than 10 seconds it's generated, for a video in less than a minute! Below is the input: a dress laid flat, and output: a full video shoot
Starting today in the U.S., you can try clothes on virtually in Labs. 👕 Say you see a great shirt, but you’re not sure if it’s right for you. Use our new try on tool to upload a picture of yourself and get a feel for what the product might look like on *you.* https://t.co/kPgXxrncg0
Try it on. Try Doji. Create your AI likeness, try on real clothes, build new looks and shop your favorites. Available now in the App Store – repost / reply for an invite. https://t.co/zQf58hoBha
✨Model Update✨ @FASHN_AI Try-On v1.5 is now LIVE on @fal! Get ready for a major upgrade to your virtual try-on experiences. Try-On 1.5 brings significant improvements in speed, quality, & ease of use with a new segmentation-free approach! https://t.co/8P1i0sLI3e
A common pattern in consumer AI over the last couple years: An app that generates AI portraits of you will go viral—but then users churn after a few days. I started advising one of these apps last year called @vybeappp and the goal was to turn it into a durable app. We started with this question: In what context would people need generative portraits on a recurring basis? The founder @mandelapatrick_ dug into the data and found that some users were sticking around: they were trying on different clothes using the app. So we redesigned the app to be exclusively focused on this use-case. But most importantly, we integrated it into their existing patterns of behavior: a mobile safari extension that would intercept the user every time they were shopping. Just tap a button to try on the item on any page. They just shipped it and the results blew past all expectations: Retention nearly 4x. Once the user enabled the extension, they were essentially retained for life. And even better, it unlocked a better revenue stream: instead of a subscription that users would inevitably cancel, VYBE simply collects a commission in the background off every purchase into perpetuity.