Fashion commerce infrastructure

Make “Will this suit me?” answerable.

Veyra gives fashion retailers a customer-ready try-on and styling layer. Shoppers see themselves in the product, build a complete look, and buy with more confidence — inside the storefront you already run.

Plan a 5-SKU pilot See the customer journey

Your brand and interface stay in front
Start with one measurable surface
Performance measured on your traffic

ARC / 01NEW SEASON

OUTERWEAR / 024

Field Jacket

Washed cotton · relaxed structure

SMLXL

See this on youUse one photo. Keep shopping.

PDP

YOUR UI

One connected customer journey.Commerce-native intelligence.A confidence layer inside commerce.

The customer journey

Useful at the exact moment confidence matters.

Veyra meets shoppers inside the journey they already know. It adds personal proof to the product page, helps complete the cart, and keeps serving the purchase after it arrives.

Build confidence early

See the product on a familiar body.

The try-on action sits beside the purchase decision, directly inside the familiar product experience.

NOON / FORMBag 01

Relaxed fit · grey

Quads Line Shirt

Product detail stays exactly where the shopper expects it.

What the market learned

Personalization gets stronger as the shopper gets closer to the image.

Breuninger explored three levels of virtual try-on. Customer feedback highlighted the most personal experience: people valued seeing themselves in the product.

Read the Google Cloud retail case study

01
Catalog-ready
Prepare consistent product imagery at scale from your existing catalog assets.
Batch
02
A relevant body
Use a body type or reusable avatar that makes drape easier to imagine.
On request
03
Be your own model
Let the shopper use their own image for the most personal proof.
Personal

One system, four jobs

Everything around the render matters.

High-quality try-on comes from a complete workflow. The product image, garment roles, customer input, response time, and review path work together to earn trust.

See it on me

A shopper uploads a photo once, then tries single pieces or compatible layers inside the product journey.

Reusable avatar · multi-garment rules · fidelity review

Style the whole decision

Recommend complete looks from the catalog using the weather, occasion, preference, and what the shopper already selected.

Ranked combinations · missing-piece detection · clear rationale

Prepare every product

Turn inconsistent uploads into clean cutouts and a consistent studio presentation before they reach the customer experience.

Garment analysis · background removal · visual QA

Keep your storefront

Use the API behind your own interface or start with a focused surface. Image work runs asynchronously, so the page stays responsive.

Documented schemas · queued image jobs · usage visibility

Current retail evidence

The signal is getting stronger. Your pilot makes it specific.

Recent retailer deployments point to gains across conversion, margin, and return behavior. A focused pilot measures the impact across your catalog and customer mix.

Google Cloud × Breuninger6-week A/B test

Higher conversion. Stronger contribution margin.

During Black Week and the holiday season, shoppers who used Breuninger’s personalized virtual try-on converted at a higher rate and generated stronger contribution margin. Surveys also highlighted image quality and personalization.

The published evidence is directional across conversion and contribution margin.

View source

ZalandoJune 2026

From pilot signal to retail scale.

Up to 40%fewer returns in recent Virtual Fitting Room pilots

2026 rolloutScaling to millions of customers

Zalando is taking the experience from temporary tests to a permanent product, beginning with jeans and expanding the available assortment.

The 40% figure is a retailer-reported pilot result; the scaled rollout is now underway.

View pilot result View scale update

For product and engineering

Your customer sees the experience. Your team keeps control.

Use Veyra behind your storefront, app, or internal catalog tools. Start with a widget-sized surface or build directly against the API.

Existing product pages stay intact
Image jobs return immediately with a job ID
Garment compatibility is validated before generation
Usage and quality review travel with the response

try-on.tsInteractive job

// Queue the work and keep the PDP responsive
POST /ai/jobs/try-on

{
  "quality_profile": "interactive",
  "garments": [
    { "role": "base_top" },
    { "role": "outerwear" }
  ]
}

// 202 Accepted
{ "status": "queued", "job_id": "..." }

Storefront stays responsive

Start focused. Learn fast.

A useful first pilot fits on one page.

Pick one customer moment, a small representative catalog slice, and one business question. Create a focused learning loop that shows how personal proof changes purchase behavior for your shoppers.

Choose the momentProduct page try-on, cart styling, or catalog preparation.

Choose the sliceFive to twenty-five SKUs that represent real catalog complexity.

Choose the measureActivation, add-to-cart, conversion, contribution margin, or returns.

Take the next useful step. Copy a seven-line brief your commerce, product, and analytics teams can fill in together.

Useful questions