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ViSenze

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Revolutionize e-commerce with AI-driven smart search and insights.

enterprise· for enterprise

ViSenze handles visual and multimodal product discovery for large retail catalogs, letting shoppers search by image, text, or a combination across millions of SKUs. The platform auto-tags products using generative AI, powers similar-item and complete-the-look recommendations, and surfaces discovery analytics for merchandisers. It targets enterprise retail and marketplace teams — heads of ecommerce, search, and merchandising — who need catalog-scale visual search without building computer vision infrastructure in-house.

> pick this if

Pick this if you're an enterprise retailer or marketplace with a million-plus SKU catalog where visual discovery, multimodal search, and catalog-wide attribute enrichment are material revenue levers and you don't want to staff a computer vision team.

> look elsewhere if

Look elsewhere if you're sub-$10M GMV, run a small curated catalog where keyword search and manual merchandising are sufficient, or need a self-serve, transparent-pricing search tool you can deploy without an enterprise procurement cycle.

> ViSenze is used by

  • Glami
  • AJIO
  • DFS
  • Myntra
  • Rakuten
  • Meesho
  • Lotte Homeshopping
  • Zalora
  • Tod’s
  • Urban Outfitters
  • Shinsegae
  • Target
  • Mango
  • Showpo
  • Hepsiburada
  • EyeBuyDirect
  • Myntra
  • Zalora
  • ShowPo

> ViSenze is built for

  • DTC apparel & fashion
  • home & furniture
  • marketplaces

> what it does for ecommerce

  • Search catalogs by image, text, or combined multimodal queries
  • Auto-generate product attributes and tags using GenAI vision models
  • Serve similar-item and complete-the-look recommendations across PDP and PLP
  • Surface search and discovery analytics for merchandising decisions
  • Deploy at marketplace scale across millions of SKU variants

> how you'd use it

  • Fashion marketplace, $200M+ GMV, 15-person search & discovery team
    Replacing a keyword-only search stack with image + text multimodal queries across 5M+ SKUs from 2,000 third-party sellers with inconsistent attribution
    → Cuts zero-result rate on long-tail visual queries, and GenAI tagging normalizes seller-supplied metadata without a manual taxonomy project
  • Home and furniture retailer, $80M GMV, 4 merchandisers plus a 2-person data team
    Adding complete-the-look modules to PDPs and similar-item carousels to PLPs for a catalog where shoppers browse by style rather than SKU name
    → Higher PDP-to-cart rates on discovery surfaces and merchandisers get attribute-level analytics on which visual patterns convert
  • Apparel retailer, $300M GMV, enterprise ecommerce org with in-house dev but no CV team
    Shipping camera-based search in the mobile app and auto-enriching 500K seasonal SKUs with color, pattern, silhouette, and neckline attributes
    → Ships visual search in a quarter instead of building a CV pipeline, and attribute coverage jumps from ~40% to near-complete across the catalog

> ViSenze use cases

> ViSenze key features

  • Multi-Search Capabilities
  • Smart Recommendations
  • GenAI Tagging
  • Analytics and Insights

> how visenze compares

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> alternatives to ViSenze in our index

by shared use-case

> ViSenze pairs well with