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The Top Five Startups from New York Fashion Tech Lab 2018(Forbes)

July 17, 2018

New York Fashion Tech Lab's cohort of eight entrepreneurs on stage at Demo Day 2018.YUMI MATSUO/SPRINGBOARD ENTERPRISES FLICKR.

 

The article first appeared on the Forbes.

 

This summer, New York Fashion Tech Lab (NYFTL) graduated its fifth annual cohort of nine women-led companies. Co-founded and produced by non-profit venture catalyst Springboard Enterprises, NYFTL unites cutting-edge startups with established retail companies to facilitate the conversations that will steer the future of fashion. 

 

The program is sponsored by leading fashion companies such as Bloomingdale's, LVMH, Macy's and Tory Burch, who collectively select each year's cohort of startups. NYFTL Managing Director Jackie Trebilcock says NYFTL's retail partners are looking for B2B startups with solutions that can help solve a problem.

 

"The companies get to work with retailers and brands for twelve weeks, during which we want to foster collaboration and open innovation," says Trebilcock. "Some companies use NYFTL as an opportunity to get in front of more retailers and brands, and others use it as a jumping-off point into the fashion industry."

 

Here are five of the most promising companies from FTL’s 2018 cohort that are using innovative technologies to reshape the fashion industry:

 

Cherrypick.ai

Founded in 2017, New York-based Cherrypick.ai turns comments on Instagram into sales leads for brands. “Tracking product intent across social media is the new metric to understanding business performance, because intent is predictive of sale,” says co-founder and COO Melissa Munnerlyn. Cherrypick.ai is building the deepest data set of consumer intent in the beauty industry, offering clients real-time insights into the products within their categories that they are competing with, and the brands that claim the most “intent”—and consumer dollars—at a given time.

 

Using natural language processing software to decode the thousands of comments left on brands’ Instagram posts each day, Cherrypick.ai integrates with marketing tools to trigger customer-specific alerts. In other words, the heart-eye emojis you posted on a cult beauty brand’s latest Instagram on your lunch break might just be responsible for the email that just landed in your inbox.

 

“There is so much value trapped in these comments and it is difficult for a brand to extract it at scale,” says Munnerlyn. “Tracking product intent is the key to unlocking the true value of social media.”

 

Prior to FTL, Cherrypick.ai raised $260,000 from XRC labs and angel investors last year, and will close its $1 million seed round by the end of 2018, including investment from Brilliant Ventures.

 

EverThread

EverThread renders product images at a fraction of the cost of producing images manually. “There aren’t enough images of products shown online because of the cost and time it takes to produce those images,” says founder and CEO Nicole Mossman.

 

EverThread’s technology allows retailers to merchandise products in a way that resembles a real-life, at-home experience. In one example, a couch, carpet and set of cushions laid out in a living room can be toggled by the customer to visualize different color combinations. These contextual images, Mossman says, lead to increased conversions and higher average order value.

 

“If a product is available in many configurations and colors, and retailers want to show each product from three different angles, this can yield over 22 million unique images which cannot be produced using traditional methods,” Mossman says. Large fashion companies with several product variations face the same challenge, and Mossman credits NYFTL with providing insight into how the fashion industry might use the company’s technology.

 

Prior to NYFTL, EverThread raised approximately $650,000 over three years: an equity round in 2015 and a convertible note in 2016-17. The company is currently closing a bridge round that will bring total fundraising over $1 million.

 

Read more on the Forbes.

 

 

 

 

 

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