Fashion Tech Startup: Meet

Fashion Tech Startup: Meet

A witty, fashion-focused chatbot? Sounds like something we should look at! New York City based startup has made a shopping search engine where their users “like” products and their system is able to curate items to their taste and style. We spoke with Charese Embree,’s co-founder, who told us more about what they have created.

Describe is a smart shopping search engine that brings the personal shopper experience online. The user types in an initial search item (e.g. brunch wear, cocktail dress or evening gown). They then “like” a few products that fit their personal style and that are similar to what they have in mind. uses machine learning technology and natural language processing to figure out what characteristics the shopper is looking for and shows them items they will like.

What was the inspiration behind creating

My co-founder Adam and I developed the idea when we lived together in San Francisco. I worked in luxury retail, and I would tell Adam how frustrating it was to compete with online retailers. After many months of brainstorming over glasses of wine, we knew we needed to change the way people shopped online. We started thinking of ways to bring my background in retail fashion and his background in computer engineering and coding into one forum.

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Tell us about your website and Fyndbot. is an online personal shopper available on mobile and on desktop. The user either types in what they are looking for or shops one of our specialty categories. From there, analyzes the items the customer “likes” and narrows down clothing options to find the perfect item. makes it quick and easy to shop for clothing online without having to browse thousands of items, through hundreds of pages on multiple websites.

The Fyndbot is an extension of that can have human-like conversations. The Fyndbot is available on Facebook Messenger or on’s Facebook page. To use the Fyndbot, users do not need to be a fashionista with an extensive vocabulary of clothing terms. The user tells Fyndbot what they’re looking for, just as they would a personal shopper. The Fyndbot then presents options, and the shopper clicks to choose their favorite. Through this process, the bot learns the shopper’s taste. and Fyndbot share a search engine, so the Fyndbot shows the user the same inventory of dresses they can see on

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What value does have that makes it stand out against other startups in the space?

Adam and I bring different backgrounds to, and that’s what makes the project work and stand out. Adam single-handedly built’s search engine from the ground up, while I was able to advise him on all things fashion-related. Adam conducts extensive research to ensure that’s natural language processing and machine learning capabilities are better than its competitors’. We have noticed that many fashion shopping sites are strictly built by engineers. They lack the fashion feeling and knowledge of how people shop that offers.

What has been the hardest obstacle for you in starting What has been your favorite part?

Our biggest obstacle was learning to manage our expectations. What we expected our customer acquisition rate to be and what it was were very different. At this early stage, it has allowed us to be more connected with our users, talk to them, get their feedback and really bring the personal shopper to the web. It helps show our customers that we are people, not just a website. We care about what they say and what we can do to improve the customer experience. In fact, staying connected with’s customers is one of my favorite parts about running the business. I reminds me what I loved about working in retail.

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What can we expect from in the future?

Right now, carries women’s dresses from Nordstrom and Bloomingdale’s. We are in the process of adding all categories of women’s and men’s clothing to our site and Fyndbot, so we will have the full breadth of options that you would find in a department store. Once we expand our product categories, we will add more retail partners to the site.

Learn more about by visiting their website.

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