Fitrove - Thrift & Style AI

Vintage ID, outfits, archive

Free · In‑App Purchases · Designed for iPad. Not verified for macOS.

Identify vintage clothing from photos, explore era, style, and key details, and keep smarter notes for every thrifted find. Discover the story behind every secondhand find. Fitrove is an AI-powered thrift, vintage, and archive fashion assistant. Upload a photo of a clothing item, accessory, label, or style reference, and Fitrove helps you understand what you are looking at before you buy, save, or style it. Whether you are browsing a thrift store, checking an online listing, building your wardrobe, or learning more about archive fashion, Fitrove gives you a clearer read on each piece. What Fitrove Can Do Identify Vintage and Secondhand Pieces Upload a photo and Fitrove will analyze visible details such as silhouette, fabric, construction, labels, hardware, print, pleating, and era signals. The app gives a cautious read instead of overclaiming exact brands or dates. Understand Brand and Designer Context Fitrove helps explain possible brand references, designer context, line information, and style codes. If a brand is uncertain, Fitrove will show confidence levels and explain what evidence is missing. Estimate Market Price Get an estimated market price range, not a single fixed number. Fitrove highlights price risks, condition concerns, and what to check before paying more. Style Your Finds Turn one thrifted piece into outfit ideas. Fitrove suggests styling formulas, what to avoid, missing pieces to look for, and ways to make the item fit your personal wardrobe. Build Your Archive Save analyzed pieces into your personal archive. Track categories, brands, eras, aesthetics, notes, and photos so your wardrobe becomes easier to understand over time. Discover Your Personal Style Upload a style reference photo and Fitrove can summarize your style keywords, recurring aesthetics, color palette, silhouettes, brand patterns, era patterns, what to look for next, and what to stop buying. Who Is Fitrove For? Thrift Shoppers Use Fitrove in-store to decide whether a piece is worth buying. Vintage Lovers Learn more about eras, labels, silhouettes, and design references. Resellers Check price risk, market range, and condition flags before listing. Fashion Learners Build visual knowledge around archive fashion, secondhand pieces, and styling. Why Use Fitrove? Fitrove helps with secondhand shopping: Clearer: Understand what a piece might be and why it matters. Faster: Get a quick buy, consider, or pass read while shopping. Smarter: See confidence levels, price risk, care advice, and styling potential. Personal: Build an archive that reflects your own taste. Start building your fashion archive with Fitrove today. [About Fitrove Premium] • Payment will be charged to your iTunes Account at confirmation of purchase • Subscription automatically renews unless auto-renew is turned off at least 24 hours before the end of the current period • Your account will be charged for renewal within 24 hours before the end of the current period • Any unused portion of a free trial period, if offered, will be forfeited when the user purchases a subscription • Subscriptions may be managed by the user, and auto-renewal may be turned off by going to iTunes Subscriptions after purchase Terms of Use: https://app-service.getvintora.com/static/user_agreement_20260203.html Privacy Policy: https://app-service.getvintora.com/static/privacy_policy.html

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The developer, PIXELCELL.LIMITED, indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .

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Information

Seller
  • PIXELCELL PTE. LIMITED
Size
  • 100.7 MB
Category
  • Reference
Compatibility
Requires iOS 17.0 or later.
  • iPhone
    Requires iOS 17.0 or later.
  • iPad
    Requires iPadOS 17.0 or later.
  • Mac
    Requires macOS 14.0 or later and a Mac with Apple M1 chip or later.
Languages
  • English
Age Rating
4+
In-App Purchases
Yes
Copyright
  • © 2026 PIXELCELL PTE. LIMITED
  • Privacy Policy

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