AI Technology Behind TryPoint

TryPoint uses Google's virtual try-on AI models to generate realistic previews of shoppers wearing your garments. Here is how the technology works and why it produces accurate results.

Google's virtual try-on models

TryPoint is powered by diffusion-based AI models from Google, trained specifically on fashion data. These models understand how different fabrics behave on different body types: how they fold, stretch, drape, and wrinkle.

The result is a try-on preview that looks natural rather than like a flat image pasted onto a photo. Garment details like prints, logos, stitching, and texture are preserved in the generated image.

How a try-on is generated

1. The shopper uploads a photo of themselves.
2. TryPoint's AI analyzes the shopper's body shape and pose.
3. The AI maps the selected garment onto the shopper, adjusting for body shape, fabric behavior, and lighting.
4. A realistic preview is generated in seconds.

All processing happens on Google's cloud-based AI infrastructure. No heavy computation runs on the shopper's device or your store.

What makes it accurate

Fabric understanding. The AI knows how different materials behave. A silk dress drapes differently than a wool jacket, and the model reflects that.

Body adaptation. The AI adapts to different body shapes and poses. Results are personalized to each shopper, not a one-size-fits-all overlay.

Detail preservation. Prints, logos, buttons, zippers, stitching, and texture from your product photos are maintained in the try-on output.

Back-view support. Shoppers can see how a garment looks from behind, not just the front. This is especially useful for swimwear, evening wear, and jackets.