PARIS — Lily AI, a product attributes platform that ensures fashion companies and consumers speak the same language, has closed a $25 million Series B round.
The round saw the participation of new and returning investors including Canaan Partners, Conductive Ventures, Sorenson Ventures and New Enterprise Associates.
The new financial backing is meant to support the California-based start-up’s plans to grow its business further into mid-market retail e-commerce brands; branch out into home and beauty, and expand geographically, with an eye toward the U.K. and Europe. It also plans to offer further applications within the retail stack.
Lily AI was created in 2015 by entrepreneurs Sowmiya Chocka Narayanan and Purva Gupta as an AI-empowered app with emotional intelligence for fashion shoppers, with initial funding from investors such as Unshackled Ventures, an early-stage venture capital fund for immigrant-founded start-ups.
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Initially, the female-led company looked to build an emotional intelligence-powered shopping experience, available through an iOS app, that used machine learning to understand a woman’s preference and body perception to offer confidence-boosting recommendations.
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Its seed funding round led by NEA and Unshackled Ventures raised $2 million. In 2020, it secured $12.5 million in Series A funding from Canaan Partners, NEA and Fernbrook Capital Management, which allowed the company to pivot from its earlier app-based solution toward an enterprise product offering that focuses on creating customer-centered product taxonomies to improve e-commerce site search, demand forecasting, merchandise planning, product recommendations and discovery as well as search engine optimization and marketing.
“The language of the consumer is basically where we use deep image recognition technology [and] industry-leading AI capabilities [to] read images and text, extracting attributes that matter to the end consumer,” Gupta, the company’s chief executive officer, explained to WWD.
Gupta said the Series B funding arrives “at an interesting point where we have proven with the first few applications [where] we’ve been able to solve a technology problem through image recognition.” It has then shown fashion companies the impact that feeding the resulting product attributes could have on the short term, which the executive estimated at up to 10 percent of a business’ revenue. It counts Bloomingdale’s, Gap Inc., Macy’s and ThredUp among its U.S.-based clients, and the executive said they were in talks with “a very large U.K.-based retailer.”
The key learning of what Purva deemed a “really good validation and product market fit” phase is that “it’s become very evident that product attributes are really underused, which is a massive opportunity for retail,” she continued, where in time, the taxonomies developed using Lily AI could impact the whole retail value chain, influencing anything from assortments offered to the copy written in product descriptions.
Gupta said Lily AI was a lone player that addressed the quality of the data being fed into systems, a pain point for companies, which are constantly challenged to upgrade their enterprise tools across the retail value chain.
“Nobody wanted to solve the hard problem and do the dirty work. You get a new search engine, you get a new recommendation engine, you get a new demand forecasting application [and] the first thing that they asked the brand or retailer is ‘can you give me your product attribute data?’ That today is being done manually [using] vernacular, inaccurate, incomplete [taxonomies], so everybody is just building on top of bad data,” she said.
Describing founders Gupta and Narayanan as “leaders capable of redefining a sector” who “developed a world-class, scalable platform that’s reinventing modern retail,” Maha Ibrahim, general partner at Canaan, stated that “Lily AI has proven the power of product attribution in empowering shoppers, boosting conversions and increasing revenues for some of retail’s most admired brands. We’re excited to see what’s next.”