TryItOn
Stop guessing & wasting money on returns. Try on with AI.
What it does
Stop guessing & wasting money on returns. Try on clothes with AI, build a digital wardrobe from the clothes you own, and plan outfits before you wear or buy them. TryItOn saves the average shopper almost $500 a year in returns & poor styling while upgrading your fashion sense. If you’ve always loved online shopping but hate buying clothes on a hope & a prayer, TryItOn is for you.
TryItOn is the AI fitting room that shows how clothes, shoes, eyewear, hair and more actually look on you, before you buy — anywhere you shop.
The AI fitting room that shows you how clothes actually look on you, before you buy. One click on any garment, any storefront, any device. Your AI fitting room follows you everywhere you browse. It’s as easy as 1, 2, 3, 4 — from outfit to mirror in four small steps. Click any garment, eyewear, shoe or accessory online — or upload your own. Fabric, drape and lighting redrawn onto you in seconds. No filters, no awkward overlays. Every try-on lands in your wardrobe. Share with a friend, then buy with confidence. Skip the gamble. TryItOn renders a photorealistic preview of any garment on your body in under ten seconds. No packing returns, no waiting two weeks for the right size. Stop guessing…from tryiton.now
Does the same job
all alternatives →More commerce this month
the category →

Compare your startup equity grant for free.
Commerce · 26d ago · equitybee.com
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com