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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. 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 more durable than she anticipated. I had breakfast not too long ago 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 folks truly discover helpful.T
Her story helps clarify one thing. My first publication of 2025 introduced that it could be The 12 months 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 examine after examine has proven that the know-how 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 tasks delivered no measurable worth. I do suppose 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 means of provides some hope that persistence and endurance would possibly certainly make these breakthroughs occur.
Fashionista Fail
Bornstein’s authentic pitch to VCs appeared apparent: Use AI to unravel tough vogue issues by matching prospects with the right clothes, which they’d be delighted to pay for. (Daydream would take a minimize.) You’d suppose the setup can be easy—simply connect 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 straightforward half. It seems that fulfilling even a easy request like “I would like a gown 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 wish 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 person in Daydream’s long-extended beta take a look at would say one thing like, “I’m a rectangle, however I would like a gown to make me seem like an hourglass.” The mannequin would reply by displaying clothes 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 group. In December 2024 she employed Belousova, the previous CTO of Grubhub, who in flip introduced in a group of high engineers. Daydream’s secret weapon within the fierce expertise struggle is the prospect to work on an interesting drawback. “Style is such a juicy area 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 deciphering what the shopper says after which by matching their typically quirky standards with the wares on the catalog aspect. With inputs like I would like a revenge gown for a bat mitzvah the place my ex is attending along with his new spouse, that understanding is important. “We’ve this notion at Daydream of customer vocabulary and a service provider vocabulary, proper?” says Bornstein. “Retailers communicate in classes and attributes, and buyers 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 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 means,” she says. A buyer would possibly share a particular coloration or present a necklace that they’ll be carrying.
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. “Each makes a specialised name. We’ve one for coloration, 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.
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