About us

After 30 years of combined experience, two founders, and countless prototypes later, YesPlz AI was born from a simple word: frustration. Despite spending years working on some of the most advanced tech products on the market, Jiwon and Sukjae struggled to perform a simple task: to find a plain white t-shirt. Anyone who has tried to find clothing online knows the particular type of frustration that comes with typing and re-typing keywords into a search engine, only to receive thousands of irrelevant search results. 

Typing traditional keywords into search engines isn’t effective. It requires rich and accurate text information about the product, that the average user doesn’t know. And, besides accuracy, users are expected to know the vocabulary of fashion brands. 

From a retailer point of view, updating text-based keywords takes hours of intensive labor. With new product description updates on the daily, text-based search also frustrates retailers.

And so, the mission was born: to transform fashion ecommerce search like never before. 

Jiwon and Sukjae combined elements of search that had never been blended: visual search and artificial intelligence. Jiwon, a product manager for Samsung SmartTV and Sukjae, a machine learning specialist and a software engineer for Microsoft and various tech startups, used their backgrounds to build a solution that was high-tech, but easy for users to navigate. 

Through extensive user interviews, they learned that users have unique preferences when it comes to style. Even a simple white t-shirt can have different cuts, fits, and styles. 

After carefully studying current search solutions, Jiwon and Sukjae realized that all of the search solutions on the market fell short in meeting customer needs. Current solutions still didn’t solve the complex nature of text-based search for retailers--and weren’t user-friendly.

And so, YesPlz AI was created. Through the YesPlz Style Filter, customers can search for clothes in a way that mirrors the intuition that comes with shopping in-store. No need to type in long, rich keyword combinations. Just select the style on a virtual mannequin and artificial intelligence can find the appropriate products. 

With a 1 second learning curve, the YesPlz Style Filter allows users to visually search for products and filters based on their preferred attributes. 

YesPlz AI has now expanded to include product recommendations, user insights, and add-ons such as Complete the Look. With proven success, YesPlz AI is excited to help more ecommerce partners and their end customers have a delightful search and recommendation experience while shopping.

Founding Members
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Jiwon Hong
Jiwon’s experience working as a product manager for Samsung and Sony Music inspired her to create a recommendation engine that connects the online marketplace through smart, sleek, and intuitive search experience.
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Sukjae Cho
Sukjae’s specialization in applied AI, combined with his experience as a software engineer for Microsoft and various tech startups, is what keeps YesPlz running smoothly.
Victoria Garcia @Marc Jacobs, Saks
Nidhi Desai @Rakuten, ShopRunner, Hudson's Bay
Eva Neumann @FarFetch
Brian Alenduff @Everlane

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