Snap’s visual algorithms were invented and coded by 27-year-old founder Jenny Griffiths, while completing a Master’s degree in Computer Science.
She says: “We wanted to create a brand that really resonates with twenty and thirty-somethings. We held a load of focus groups and found that men don’t look to celebrities for their inspiration, but their peers.” So the “Trending” page pulls results of trending products that can be purchased by guys.
“Snap Fashion for Men” uses computer vision technology to find similar items of clothing to those in a photograph, whether it’s been taken on a phone or found online. Results are based on the cut, colour and texture of the photographed item. Its algorithms search major retailers and refine results by different categories of clothing including, outerwear, formal wear, trousers, tops, shorts, accessories and shoes to a range of similar items.
Snap Fashion claims to be different because it also does ‘shape matching’ and is more cross-platform than competitors.
So far the startup has raised £300,000k from Venrex in 2012, and now claims to be in profit. Snap Fashion was founded in 2011 and launched fashion’s first visual search engine in 2012.
Competitors include ASAP54, a former TechCrunch Disrupt Battlefield Alumni which launched this year. Also, Cortexica launched Style Thief this year after licensing out some technology. And Slyce raised significant funding over in the U.S.