Shopant lets users turn saved TikTok, Instagram, or Pinterest posts into purchasable outfits by extracting each piece and matching it to real store products. Users can assemble the items on a personal avatar to preview the full look before adding items to a unified wardrobe cart for later comparison and purchase.
Funding
Funding not disclosed
Founders
Product
Problem
Social media users often discover outfit ideas on TikTok, Instagram, or Pinterest but must manually locate each item across multiple retailers, leading to a fragmented and time‑consuming shopping experience.
Solution
Shopant streamlines this workflow by allowing users to forward saved social posts to the platform, where the system extracts individual clothing pieces and matches them with real‑world products from partnered stores. Users can select the relevant slides, view the matched items on a virtual avatar, and preview the complete ensemble before purchasing. The platform also stores the curated looks, enabling shoppers to compare options, build a persistent wardrobe collection, and return to saved outfits for future purchases.
Target Audience
Shopant targets fashion‑forward social media users and online shoppers who curate outfit inspiration from visual platforms and want a consolidated, try‑on enabled purchasing process.
Features
- Automated image analysis that isolates apparel items from TikTok, Instagram, and Pinterest posts
- Product matching engine that maps extracted items to inventory from multiple online retailers
- Virtual avatar try‑on that assembles selected pieces into a full outfit for visual preview
- Persistent “stash” where saved looks and their source links are organized for later review
- Integrated cart creation that consolidates chosen items for a single checkout flow