In Short
Most lingerie & intimates teams know the pattern: plenty of browsing, plenty of returns, and a fuzzy picture in between. For lingerie & intimates, the moment a shopper imagines a piece on their own body is the moment a sale is won or lost. Fit and confidence have quietly become the biggest swing factors in lingerie & intimates. Expectations in Lingerie & Intimates have shifted, and the tools brands use to show their pieces have to keep up. The way a lingerie & intimates brand lets people picture a garment on themselves says a lot about how it converts.
The Question Behind It
For a Director of 3D Production, per-session cloud-gpu bills that punish every try-on is more than an annoyance — it is a steady drag on conversion and margin. It rarely starts as a crisis; per-session cloud-gpu bills that punish every try-on builds quietly until a returns report or a soft launch makes it impossible to ignore. A recurring challenge for lingerie & intimates is per-session cloud-gpu bills that punish every try-on. The issue shows up most clearly as Per-session cloud-GPU bills that punish every try-on after a disappointing returns quarter.
What People Ask
Is Mirari photoreal? Mirari is a live, expressive on-body try-on — an AR "mirror" plus a rigged 3D avatar. A photoreal native-GPU tier is on the roadmap; the shipping experience is designed to stay $0 cloud-GPU.
Will it fit our 3D assets? Yes — Mirari imports standard glTF/GLB garments and exports USDZ for Apple AR Quick Look, so it fits an interoperable pipeline.
Can my team design in it too? Yes. The Design Studio recolors, re-fabrics, places prints, switches colorways and even generates garments from templates — then pushes them straight to the try-on catalog.
Does it need an app or a powerful phone? No — Mirari runs in the browser with an adaptive quality governor that keeps it smooth from mid-range phones to flagship hardware, and it falls back gracefully without a camera.
Mirari, Explained
Rather than another flat gallery, Mirari puts the garment on the shopper’s own body, live, with their real arms and hair in front of the cloth. Mirari pairs a believable try-on with a design studio, so the same tool that shoppers try on in is the one your team designs in. Mirari tackles this with On-device pose, face & hand tracking: Pose, face and hand landmarks are solved in the browser each frame, so the try-on reacts to the shopper instantly with no server round-trip. Since on-device pose, face & hand tracking sits within the AI Perception part of Mirari, it fits naturally into how lingerie & intimates teams already work. Because perception and rendering run in the browser, the experience feels instant — and it costs nothing in cloud GPU.
The Impact
The result is a connected design-to-storefront workflow, without a render farm or a per-session GPU bill. Try-on stops being a gimmick and starts being a default on every product page. The numbers follow the confidence: higher add-to-cart, fewer bracketed orders, and drops that land. Shoppers get a believable look at the fit; the brand gets fewer returns and more confident checkouts. Brands using this approach see A connected design-to-storefront workflow with a lean team.
Try Mirari
Stop relying on flat product photos. Mirari, built by ZadeNor AI, brings a believable on-body try-on, real-body occlusion and a recolor/print/template design studio into one app that runs on any device. Try it free.
Over time, per-session cloud-gpu bills that punish every try-on translates into bracketed orders, costly reverse logistics, and drops that never find their audience. Every shopper who cannot picture the fit is a basket left half-built. Teams end up reshooting and discounting instead of merchandising with confidence. Brands using this approach see A connected design-to-storefront workflow with a lean team. The numbers follow the confidence: higher add-to-cart, fewer bracketed orders, and drops that land. For lingerie & intimates, that means a connected design-to-storefront workflow the whole team can rely on.
What looks like a product-page problem is often a fit, confidence and returns problem in disguise. Over time, per-session cloud-gpu bills that punish every try-on translates into bracketed orders, costly reverse logistics, and drops that never find their audience. Brands using this approach see A connected design-to-storefront workflow with a lean team. The result is a connected design-to-storefront workflow, without a render farm or a per-session GPU bill.
The cost of per-session cloud-gpu bills that punish every try-on is rarely a single number — it is lost conversion, return shipping, and a catalog that underperforms. What looks like a product-page problem is often a fit, confidence and returns problem in disguise. The numbers follow the confidence: higher add-to-cart, fewer bracketed orders, and drops that land. Brands using this approach see A connected design-to-storefront workflow with a lean team.
What looks like a product-page problem is often a fit, confidence and returns problem in disguise. The cost of per-session cloud-gpu bills that punish every try-on is rarely a single number — it is lost conversion, return shipping, and a catalog that underperforms. For leaders, the real risk is strategic: a try-on gap becomes a ceiling on how far the brand can scale online. Shoppers get a believable look at the fit; the brand gets fewer returns and more confident checkouts. Try-on stops being a gimmick and starts being a default on every product page.
