Julie Bornstein thought it could 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 buying 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 patrons to find the right clothes utilizing AI.
The fact 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 sudden flip as the ladies schooled me on the stunning problem of translating the magic of AI methods into one thing individuals really discover helpful.T
Her story helps clarify one thing. My first e-newsletter of 2025 introduced that it could be The Yr of the AI App. Although there are certainly many such apps, they haven’t reworked the world as I anticipated. Ever since ChatGPT launched in late 2022, individuals have been blown away by the methods carried out by AI, however examine after examine has proven that the expertise has not but delivered a major increase in productiveness. (One exception: coding.) A examine revealed 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, but it surely’s taking longer than individuals anticipated. Listening to the tales of startups like Daydream which can be pushing to interrupt by way of provides some hope that persistence and endurance would possibly certainly make these breakthroughs occur.
Fashionista Fail
Bornstein’s unique pitch to VCs appeared apparent: Use AI to unravel difficult trend issues by matching prospects with the right clothes, which they’d be delighted to pay for. (Daydream would take a reduce.) 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 outlets to retail giants, was the simple half. It seems that fulfilling even a easy request like “I want 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 dearth 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 consumer in Daydream’s long-extended beta take a look at would say one thing like, “I’m a rectangle, however I want a costume to make me appear like an hourglass.” The mannequin would reply by displaying attire with geometric patterns.
In the end, Bornstein understood that she needed to do two issues: postpone the app’s deliberate fall 2024 launch (although it’s now out there, Daydream continues 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 high engineers. Daydream’s secret weapon within the fierce expertise struggle is the possibility to work on an enchanting downside. “Trend is such a juicy area 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 unravel this downside twice—first by deciphering what the client says after which by matching their generally quirky standards with the wares on the catalog aspect. With inputs like I want 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 consumers 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 really 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 really 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. “Every one makes a specialised name. We now have one for colour, one for material, 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 viewpoint. Google’s Gemini is much less so, however it’s quick and exact.
