End sizing guesswork. Boost profits . Reduce waste.

Hyper-accurate digital body twins for virtual try-on that actually fits.

Where It Works

Works across web, mobile, in-store, design tools, and 3D engines.

Show garments on hyper-accurate body twins for realistic drape, fit visualization, and accurate size suggestions mapped to your brand chart.

Generate precise digital measurements to streamline bespoke orders, minimize alterations, and enhance made-to-measure accuracy.

Preview drape and fit digitally across diverse body types, improve inclusivity, and reduce physical sampling for faster seasonal launches.

30% of fashion returns are due to poor fit — costing brands billions. Hyper-accurate digital body twins for virtual try-on that actually fits.

Returns from Poor Fit

Shoppers rely on guesswork because size charts vary by brand and body shape, driving misfit, returns, and lower loyalty.
High Drop-Off During Capture

Asking for measurements, app installs, or long scanning flows causes PDP abandonment—especially on mobile.
Sample-Heavy, Slow Merchandising

Producing physical samples across sizes is costly and delays seasonal launches; early, size-inclusive fit checks are limited.
Privacy & Compliance Hurdles

Body imagery and measurements are sensitive, and security reviews can stall pilots and rollouts.

Fit-True Virtual Try-On

Show garments on a SMPL-based body twin mapped to your size chart. Realistic drape and measurement mapping help customers choose the right size the first time.
App-Free Guided Capture

A sub-minute, browser-based flow from the PDP: upload a photo/video, generate the body twin, and surface a size recommendation without breaking the purchase path.
Digital Sampling Across Sizes

Preview drape/fit on realistic body twins spanning your target size range; integrate with CLO/Browzwear/engines to reduce physical samples and accelerate GTM.
Enterprise-Grade Privacy & Controls

GDPR-aligned processing with data minimisation, configurable retention/deletion, enterprise SSO/access controls, and private or regional deployment options.