Start with a selfie
One photo of you and one of the garment. The split view shows what changed.
This App Store image demonstrates the virtual try-on workflow. It is a product screenshot, not a standardized accuracy test.
Current product screens
Virtual try-on examples without invented claims
These images come from the current US App Store listing. They show the workflows available in TryOn AI. They are product examples, not evidence of physical fit or a measured accuracy rate.
Try it now
Try clothes on before buying
Point it at a product page, pick upper, lower or full body, then tap Try on.
The garment type tells the app which part of the photo should change. A clean front-facing product image gives it less irrelevant detail to interpret.
Find clothes from a screenshot
Screenshot an outfit you liked and the app finds it across stores, with prices.
The screen shows visually similar listings rather than claiming every result is the original item. Store inventory and prices can change after the search.
Check an outfit for the occasion
Tell it where you are going. It reads the look and says what is working.
The response uses the occasion entered by the user. It is a second opinion and cannot know a venue or employer dress code that was not provided.
Keep a digital wardrobe
Every try-on is saved, so you can put two options side by side.
Saved previews make it easier to compare several visual options generated from the same base photo.
What these show
A product workflow you can inspect
The screens document the input, controls and type of output available in the app. They also support the feature descriptions used across this site.
What these do not show
A controlled comparison
Marketing screens cannot establish accuracy. Read the fixed-photo test method we will use before publishing any benchmark result.
Read the test method →