Julie Bornstein thought it could be a cinch to implement her thought for an AI startup. Her résumé in digital commerce is impeccable: VP of ecommerce at Nordstrom, COO of the startup Sew Repair, and founding father of a customized procuring platform acquired by Pinterest. Style has been her obsession since she was a Syracuse excessive schooler inhaling spreads in Seventeen and hanging out in native malls. So she felt well-positioned to create an organization for patrons to find the right clothes utilizing AI.
The fact was a lot tougher than she anticipated. I had breakfast just lately with Bornstein and her CTO, Maria Belousova, to find out about her startup, Daydream, funded with $50 million from VCs like Google Ventures. The dialog took an sudden flip as the ladies schooled me on the shocking issue of translating the magic of AI programs into one thing folks truly discover helpful.T
Her story helps clarify one thing. My first e-newsletter of 2025 introduced that it could be The Year of the AI App. Although there are certainly many such apps, they haven’t remodeled the world as I anticipated. Ever since ChatGPT launched in late 2022, folks have been blown away by the tips carried out by AI, however research after research has proven that the expertise has not but delivered a major increase in productiveness. (One exception: coding.) A study published in August discovered that 19 out of 20 AI enterprise pilot initiatives delivered no measurable worth. I do assume that productiveness increase is on the horizon, nevertheless it’s taking longer than folks anticipated. Listening to the tales of startups like Daydream which can be pushing to interrupt by offers some hope that persistence and endurance may certainly make these breakthroughs occur.
Fashionista Fail
Bornstein’s unique pitch to VCs appeared apparent: Use AI to resolve difficult vogue issues by matching prospects with the right clothes, which they’d be delighted to pay for. (Daydream would take a minimize.) You’d assume the setup could be easy—simply hook up with an API for a mannequin like ChatGPT and also you’re good to go, proper? Um, no. Signing up over 265 companions, with entry to greater than 2 million merchandise from boutique retailers to retail giants, was the simple half. It seems that fulfilling even a easy request like “I want a gown for a marriage in Paris” is extremely complicated. Are you the bride, the mother-in-law, or a visitor? What season is it? How formal a marriage? What assertion do you wish to make? Even when these questions are resolved, completely different AI fashions have completely different views on such issues. “What we discovered was, due to the shortage of consistency and reliability of the mannequin—and the hallucinations—generally the mannequin would drop one or two components of the queries,” says Bornstein. A person in Daydream’s long-extended beta check would say one thing like, “I’m a rectangle, however I want a gown to make me appear like an hourglass.” The mannequin would reply by exhibiting attire with geometric patterns.
Finally, Bornstein understood that she needed to do two issues: postpone the app’s deliberate fall 2024 launch (although it’s now accessible, Daydream remains to be technically in beta till someday in 2026) and improve her technical crew. In December 2024 she employed Belousova, the previous CTO of Grubhub, who in flip introduced in a crew of prime engineers. Daydream’s secret weapon within the fierce expertise conflict is the possibility to work on a captivating downside. “Style is such a juicy house as a result of it has style and personalization and visible knowledge,” says Belousova. “It’s an fascinating downside that hasn’t been solved.”
What’s extra, Daydream has to resolve this downside twice—first by deciphering what the shopper says after which by matching their generally quirky standards with the wares on the catalog facet. With inputs like I want a revenge gown for a bat mitzvah the place my ex is attending together with his new spouse, that understanding is important. “We now have this notion at Daydream of purchaser vocabulary and a service provider vocabulary, proper?” says Bornstein. “Retailers converse in classes and attributes, and consumers say issues like, ‘I’m going to this occasion, it’s going to be on the rooftop, and I’ll be with my boyfriend.’ How do you truly merge these two vocabularies into one thing at run time? And generally it takes a number of iterations in a dialog.” Daydream discovered that language isn’t sufficient. “We’re utilizing visible fashions, so we truly perceive the merchandise in a way more nuanced method,” she says. A buyer may share a particular colour or present a necklace that they’ll be sporting.
Bornstein says Daydream’s subsequent rehaul has produced higher outcomes. (Although once I tried it out, a request for black tuxedo pants confirmed me beige athletic-fit trousers along with what I requested for. Hey, it’s a beta.) “We ended up deciding to maneuver from a single name to an ensemble of many fashions,” says Bornstein. “Every one makes a specialised name. We now have one for colour, one for material, one for season, one for location.” As an example, Daydream has discovered that for its functions, OpenAI fashions are actually good at understanding the world from the clothes viewpoint. Google’s Gemini is much less so, however it’s quick and exact.
