Editr
Head of Design + Co-Founder | Startup
2016-2018

Editr Style Discovery Engine

Editr (editr.com) was a venture-backed web-based AI-personalized shopping discovery engine where visual-style mood boards were made shoppable. Moodboards were user-curated and appeared like the pages of a fashion magazine. Editr’s visual prediction algorithm matched every mood board with continuously fresh items to shop from 2000+ brands and retailers.

Problem:  It’s exhausting to find fashion and home merch online that aligns with what you’re actually looking for. How do we give users the power to shape their own personalized shopping experience where they become the Editor (but with the magic touch of AI)? 

During our collaboration with Vogue, we built Tablo, which inspired Editr. We identified that users wanted more than images. They wanted a shopping story. We responded by turning everyone into a storyteller, into a 'fashion editor'.

Solution: Building from the ground up a web-based AI-personalized shopping discovery engine called Editr. We created something that thoughtfully leveraged computer vision (retrieval model) and machine learning to ensure that the user was provided with a fresh assortment of shoppable products.

Our early business model focused on discovery to affiliate purchases. We generated revenue through affiliates - the future vision looked to brand partnerships and real-time trend data.

Role: Co-founded AI-personalized shopping discovery engine, overseeing product design and management, UX design operations, and managing engineering team.