Julie Bornstein thought it will be a cinch to implement her concept 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. Trend 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 purchasers to find the right clothes utilizing AI.
The truth was a lot more durable than she anticipated. I had breakfast just lately with Bornstein and her CTO, Maria Belousova, to study her startup, Daydream, funded with $50 million from VCs like Google Ventures. The dialog took an surprising flip as the ladies schooled me on the stunning issue of translating the magic of AI methods into one thing individuals truly discover helpful.T
Her story helps clarify one thing. My first e-newsletter of 2025 introduced that it will 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, individuals have been blown away by the tips carried out by AI, however research after research has proven that the know-how has not but delivered a big enhance 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 enhance is on the horizon, but it surely’s taking longer than individuals anticipated. Listening to the tales of startups like Daydream which are pushing to interrupt via provides some hope that persistence and persistence would possibly certainly make these breakthroughs occur.
Fashionista Fail
Bornstein’s unique pitch to VCs appeared apparent: Use AI to unravel difficult style issues by matching prospects with the right clothes, which they’d be delighted to pay for. (Daydream would take a lower.) You’d assume the setup can 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 straightforward half. It seems that fulfilling even a easy request like “I would like a costume for a marriage in Paris” is extremely advanced. Are you the bride, the mother-in-law, or a visitor? What season is it? How formal a marriage? What assertion do you need to make? Even when these questions are resolved, totally different AI fashions have totally different views on such issues. “What we discovered was, due to the shortage of consistency and reliability of the mannequin—and the hallucinations—typically the mannequin would drop one or two components of the queries,” says Bornstein. A consumer in Daydream’s long-extended beta take a look at would say one thing like, “I’m a rectangle, however I would like a costume to make me appear to be an hourglass.” The mannequin would reply by exhibiting clothes 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 continues to be technically in beta till someday in 2026) and improve her technical staff. In December 2024 she employed Belousova, the previous CTO of Grubhub, who in flip introduced in a staff of prime engineers. Daydream’s secret weapon within the fierce expertise struggle is the possibility to work on a captivating drawback. “Trend is such a juicy house as a result of it has style and personalization and visible knowledge,” says Belousova. “It’s an fascinating drawback that hasn’t been solved.”
What’s extra, Daydream has to unravel this drawback twice—first by decoding what the shopper says after which by matching their typically quirky standards with the wares on the catalog facet. With inputs like I would like a revenge costume 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 customer vocabulary and a service provider vocabulary, proper?” says Bornstein. “Retailers communicate in classes and attributes, and customers say issues like, ‘I’m going to this occasion, it’s going to be on the rooftop, and I will be with my boyfriend.’ How do you truly merge these two vocabularies into one thing at run time? And typically it takes a number of iterations in a dialog.” Daydream realized that language isn’t sufficient. “We’re utilizing visible fashions, so we truly perceive the merchandise in a way more nuanced manner,” she says. A buyer would possibly share a particular colour or present a necklace that they’ll be carrying.
Bornstein says Daydream’s subsequent rehaul has produced higher outcomes. (Although after 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. “Each makes a specialised name. We now have one for colour, one for cloth, one for season, one for location.” As an illustration, Daydream has discovered that for its functions, OpenAI fashions are actually good at understanding the world from the clothes perspective. Google’s Gemini is much less so, however it’s quick and exact.
