Let me start with a disclaimer. My idea of “finding shoes” is finding the one pair of shoes I own in the closet. In general, I’m not much of a shopper, let alone a shoe shopper.
That said, I really love what Arlo Faria and AJ Shankar, two Berkeley PhD students on leave, have done with Modista. In their own words:
Modista simplifies online shopping by searching inventories across multiple retailers and displaying results in an intuitive interface. Our patent-pending technology organizes items according to their visual similarity using digital image processing and machine learning algorithms.
All that is true, but it doesn’t capture what makes Modista cool. Modista delivers what m c schraefel calls the “joy of search”. Even for someone like me who only buys classic black loafers, they’ve created a fun exploratory experience. To see what a real shoe-shopper thinks of it, check out this post at ShoeBlog.
I’ve been skeptical of both similarity browsing and visual search. I’m still skeptical about the breadth of either techinque’s applicability. But I am impressed with this application.
One reply on “Modista: Similarity Browsing…for Shoes!”
[…] readers may recall my post about visual search startup Modista last November, or this guest post by one of its principals. […]