Overview
YesPlz is an advanced AI-driven platform that transforms e-commerce search and discovery for fashion retailers. The software replaces rigid keyword typing with intuitive visual search tools, virtual mannequin filters, and automated apparel tagging. By understanding clothing nuances through image and text analysis, it helps shoppers effortlessly find style matches. The platform enables online stores to increase conversion rates and optimize product catalog management.
Founder: Jiwon Hong and Sukjae Cho
Popularity: Numerous active e-commerce brands and online fashion platforms globally
HQ: San Jose, California, USA
Funding: Seed funding backed by institutional investors including igniteXL
Tech stack: Python, TensorFlow, PyTorch, React, AWS
Integrations: Shopify, custom e-commerce web APIs, REST API, cloud databases
What it does
- Powers visual and text-based fashion search using artificial intelligence to understand clothing attributes and stylistic nuances.
- Provides a virtual mannequin filter allowing shoppers to visually select clothing styles without complex keywords.
- Automates product tagging, metadata generation, and catalog management for online clothing inventories.
- Delivers personalized AI fashion recommendations and complete-the-look outfit suggestions to online shoppers.
Who it's for
- Fashion E-commerce Retailers
- DTC Clothing Brands
- Online Marketplace Operators
- Digital Merchandising Teams
Why it works
- Pricing model utilizes tiered subscription plans based on e-commerce catalog size and search feature usage.
- Positioned as a fashion-native search alternative overcoming the limitations of standard e-commerce platform filters.
- Technical advantage stems from proprietary computer vision models trained specifically on apparel styles and attributes.
- Distribution scales efficiently via direct software integrations and major e-commerce platform plugin ecosystems.
Founder story
YesPlz was founded in 2020 in San Jose, California, by Jiwon Hong and Sukjae Cho after experiencing firsthand the frustration of trying to find basic clothing items online. Combining decades of experience in machine learning and product design, the founders built an intelligent visual search platform tailored specifically to solve the complexities of fashion discovery.
Comparison overview
- YesPlz provides fashion-native visual search and automated clothing tagging built specifically for apparel nuances, whereas generic search tools rely heavily on rigid text keywords. Fashion retailers choose YesPlz for specialized visual discovery and mannequin filters, though general-purpose search engines handle broader cross-industry inventory catalogs.