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 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 uncover the good clothes utilizing AI.
The truth 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 girls schooled me on the shocking issue of translating the magic of AI techniques 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 methods carried out by AI, however research after research has proven that the know-how has not but delivered a major enhance in productiveness. (One exception: coding.) A study published in August discovered that 19 out of 20 AI enterprise pilot tasks delivered no measurable worth. I do suppose that productiveness enhance is on the horizon, however it’s taking longer than folks anticipated. Listening to the tales of startups like Daydream that are pushing to break by way of offers some hope that persistence and persistence would possibly certainly make these breakthroughs occur.
Fashionista Fail
Bornstein’s authentic pitch to VCs appeared apparent: Use AI to resolve difficult style issues by matching clients with the good clothes, which they’d be delighted to pay for. (Daydream would take a minimize.) You’d suppose the setup can be easy—simply join to 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 want a costume 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 would you like 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 lack of consistency and reliability of the mannequin—and the hallucinations—typically the mannequin would drop one or two parts 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 costume to make me appear to be an hourglass.” The mannequin would reply by displaying clothes with geometric patterns.
In the end, Bornstein understood that she had to do two issues: postpone the app’s deliberate fall 2024 launch (although it’s now accessible, Daydream is nonetheless technically in beta till someday in 2026) and improve her technical staff. In December 2024 she employed Belousova, the former CTO of Grubhub, who in flip introduced in a staff of prime engineers. Daydream’s secret weapon in the fierce expertise conflict is the likelihood 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 attention-grabbing downside that hasn’t been solved.”
What’s extra, Daydream has to resolve this downside twice—first by decoding what the buyer says after which by matching their typically quirky standards with the wares on the catalog facet. With inputs like I want a revenge costume for a bat mitzvah the place my ex is attending along with his new spouse, that understanding is crucial. “Now we have this notion at Daydream of purchaser 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 am going to 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 approach,” she says. A buyer would possibly share a selected shade 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 as well as to what I requested for. Hey, it’s a beta.) “We ended up deciding to transfer from a single name to an ensemble of many fashions,” says Bornstein. “Each makes a specialised name. Now we have one for shade, 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 is quick and exact.
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