AlphaMoatによると、2026-09時点でChrome拡張機能Slidezのユーザー数は15(前月比 +15.4%)、評価は5(5件のレビュー)で、9,324件のAIブラウザ拡張機能中8,138位、業界向けサービスでは895件中761位です。
Slidezとは
AI virtual try-on for clothes while shopping online. Preview clothing from fashion websites on your own photo before buying. Virtually try on clothes from across the web before you buy. Slidez is an AI virtual try-on Chrome extension that lets you preview clothing from fashion product pages on your own photo—without waiting for each retailer to offer its own try-on tool.
Online shopping makes it easy to find clothes and hard to picture them on you. Product photos show a model; Slidez gives you a personalized visual preview so you can compare styles and decide what deserves a closer look.
HOW SLIDEZ WORKS 1. Visit a clothing product page. 2. Open Slidez and select the clothing item shown on the page. 3. Choose or upload a personal photo. 4. Generate an AI preview of yourself wearing the item.
WHY USE SLIDEZ
- Shop across brands with one virtual try-on experience
- Preview clothing on your own photo while you browse
- Compare different styles before deciding what to buy
- Use Slidez during real online shopping—not as a separate AI image editor
USE SLIDEZ TO
ストアの説明の続きを表示▾
- Compare similar pieces from different brands
- Explore a new color, cut, or style
- Narrow your shortlist before checkout
- Visualize a look when retailer photos are not enough
IMPORTANT Slidez creates an AI-generated visual preview. It does not measure you or guarantee size, fit, fabric behavior, color accuracy, or how an item will look in person. Always check the retailer’s size chart, product details, reviews, and return policy before purchasing.
Compatibility may vary by website and product page.
Slidez processes your photo and the clothing or product-page content needed to create the preview. See the Slidez Privacy Policy for details.
Install Slidez and turn the fashion pages you already shop into a more personal way to preview clothes.
拡張機能の情報
ユーザー数の推移
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+ 比較データ月:2026-09 · ユーザー数と評価はChromeウェブストアの公開データを月単位で集計したものです。詳しくはデータの方法論をご覧ください。