Finding the right dress for a summer party or a work tote that fits just so can sometimes feel less like a shopping trip and more like an endless digital maze.
That’s the headache Daydream is hoping to cure with its new shopping platform of the future, an artificial intelligence-powered service designed to make finding the perfect item feel as easy as texting a friend for style advice.
Headquartered between New York and San Francisco, Daydream invites shoppers to search the way real people talk. Rather than wade through filters, users can type something as specific as “a cocktail dress for a rooftop bar in August” or as open-ended as “a weekend getaway bag that works for the office too.” The technology understands conversational requests and quickly offers options suited to any number of unique situations.
Daydream is stepping onto a crowded field filled with tech giants already tinkering in this territory. OpenAI has launched its own shopper assistant that roams the web for users, Google has rolled out features like automated price tracking and even virtual try-ons to help consumers make choices, while Meta leverages its artificial intelligence to show more relevant ads.
Inside Daydream’s Personal Touch
What sets Daydream apart, according to founder Julie Bornstein, is a deep-rooted knowledge of what makes shoppers tick. She’s spent years shaping the digital experiences at heavyweights like Sephora and Nordstrom, and she co-founded The Yes, an earlier shopping startup that Pinterest snapped up in 2022.
“They don’t have the people, the mindset, the passion to do what needs to be done to make a category like fashion work for [artificial intelligence] recommendations,” Bornstein said. She argues that having a comprehensive catalog and serving up the right items for the right customer is crucial to making the process feel seamless.
Daydream connects users to a carefully curated roster of over 8,000 brands, from affordable basics to high fashion. The platform’s artificial intelligence processes natural language requests or even uploaded inspiration photos, then surfaces recommendations that match up. Shoppers can continue chatting with the same interface, narrowing or expanding their search just as they’d trade messages with a style-savvy friend.
As shoppers engage more, the artificial intelligence learns their preferences, getting sharper at predicting what will appeal with every search, click and save.
When it comes time to buy, customers are sent directly to the brand’s site, and Daydream takes a percentage of the sale. Bornstein is deliberately steering clear of pay-to-play ad models common in e-commerce, pointing out, “We want this to be a thing where we get paid when we show the customer the right thing.”
A recent hands-on test of Daydream managed to unearth the exactly right white cotton work shirt, but not every search result was flawless. Some dresses aimed at mothers of the bride skewed a little too close to bachelorette territory, including some in shades of white.
Bornstein says the platform’s artificial intelligence is being tweaked constantly based on how real people use it. “We want data on what people are doing so we can focus and learn where we do well and where we don’t,” she explained.
The public web version of Daydream is live and in beta, with a dedicated app expected later this year. The company has already pulled in fifty million dollars from investors, among them Google Ventures and entrepreneur Karlie Kloss.
Bornstein sees a future where personal style advice and artificial intelligence work hand in hand, helping people not just shop but rethink how they build their wardrobes.
