
Lacoste ran an extensive accuracy RFP against every sizing player on the market, including its incumbent Fit Analytics. Kleep came out on top by a clear margin, making it the straightforward choice to switch.
Read full storyOnline, shoppers cannot see how a piece falls on their own body, so they hesitate or over-order. Virtual Try-On puts the look on them in seconds, turning hesitation into confident, higher-value purchases.

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Creating your look…
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Shoppers cannot feel the fabric or picture a piece on their own body, so they second-guess the buy or order several sizes to compare at home. Virtual Try-On lets every shopper see the look on themselves in seconds, turning doubt into confidence at the exact moment it matters.
More shoppers reach checkout, baskets grow, and fewer parcels come back. Every try-on also feeds the model richer signals about your customers and how your pieces really fit.
Shoppers who see a piece on themselves buy far more often.
More product views and longer sessions on every visit.
Fewer surprises at delivery when the look is already familiar.
Virtual Try-On turns any product page into a fitting room. The shopper takes two quick photos, chooses the pieces to style together, and sees the complete look on their own body in seconds.

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Two quick pictures, straight from the product page. That is all Kleep needs to build a faithful, private model of the shopper, with no measurements and no studio booking.

Finish the Aralia Dress with the pieces that complete it




They keep the piece they are viewing and add anything else from your catalog: the shoes, the bag, the sunglasses. Kleep styles the whole outfit together, not one item in isolation.

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Seconds later the shopper sees themselves wearing the complete outfit, turning and posing. Confidence replaces guesswork, and the entire look drops into the basket in one tap.
When shoppers picture a piece on themselves, they tell you what they want, what to sell with it, and who they really are. Kleep turns every try-on into insight.
Try-on is the strongest buying signal you have.
Every try-on is a hand raised. See which products shoppers picture on themselves, and how much harder they convert.
Bundle the looks shoppers build themselves.
See which pieces shoppers style together and turn every try-on into a ready-made, higher-value bundle.
First-party taste, synced to your ad audiences.
Body, size and the styles they reach for: first-party data that turns anonymous traffic into segments you can actually retarget.
Native apps and cartridges for every major commerce platform, SDKs for your mobile apps. Live in days, not roadmaps.
One-click app from the Shopify App Store, theme blocks included, live the same day.
Read the docs →A certified cartridge that drops into your existing SFCC storefront architecture.
Read the docs →An extension built for Adobe Commerce, aligned with your deployment workflow.
Read the docs →A lightweight WordPress plugin that hooks straight into your product pages.
Read the docs →A native PrestaShop module, installed and configured in minutes.
Read the docs →A Swift SDK with native components: the full Kleep experience in your iOS app.
Read the docs →A Kotlin SDK for Android: same model, same accuracy, fully native UI.
Read the docs →Tested against the incumbents, chosen after the numbers came in. Here is how fashion’s favorite brands run sizing on Kleep.

Lacoste ran an extensive accuracy RFP against every sizing player on the market, including its incumbent Fit Analytics. Kleep came out on top by a clear margin, making it the straightforward choice to switch.
Read full story
ba&sh A/B-tested Kleep head-to-head against True Fit. Kleep converted more and returned less, with a gap wide enough to settle the decision before the test had even finished.
Read full storyKleep adapted entirely to the Victoria Beckham world, typography, tone and every detail white-labelled to the brand's own studio, giving customers a sizing experience that feels unmistakably Victoria Beckham.
Read full storyKleep cut Soeur's size-related returns, with more of the pieces customers ordered actually staying in their wardrobes, and the storefront live within a single season.
Read full storyTwo ways, and the shopper chooses. Either a 30-second questionnaire (height, weight, age, body shape) or a body scan from two smartphone photos. Our model turns that into precise measurements, then matches them against the actual measurements of each garment, not a generic size chart. The result: a recommendation per product, not per brand.
Across our deployments, brands typically see size-related returns drop 20–50% and a meaningful double-digit conversion lift, usually 15–25%, on sessions that use a recommendation. Standout deployments have reached up to 3.5× conversion among guided shoppers; exact figures depend on your catalogue, category and traffic mix. You'll see the first signal within weeks: we A/B test against your control group from day one, so every number comes from your store, not our slide deck.
Days, not quarters. We ship native apps for Shopify, Salesforce Commerce Cloud, Magento, WooCommerce and PrestaShop, plus iOS and Android SDKs. Most brands go live within two weeks. The longest step is usually your internal QA, not us. No re-platforming, no PDP rebuild.
Photos are processed to extract measurements, then deleted. We keep numbers, not images. Everything is GDPR-compliant, hosted in the EU, and your customer data is never used to train models for other brands or sold to anyone. Your data stays yours, full stop.
Like your brand. The interface is fully white-labelled: typography, colors, tone of voice, every detail adapts to your design system. Victoria Beckham's sizing flow looks designed by Victoria Beckham's studio. Yours will too.
Run the test. That's how most of our clients arrived. Lacoste chose Kleep after an extensive accuracy RFP against the incumbents; ba&sh A/B-tested us head-to-head against True Fit and the gap made the decision. We're happy to be benchmarked: garment-level accuracy is the whole product.
See the product in action and the results it delivers for brands like yours.
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