Julie Bornstein’s e-commerce startup Daydream has launched its AI-driven chatbot tailored specifically towards fashion-oriented shopping. This latest release follows a significant $50 million seed funding round secured by the company nearly a year ago.
After an initial period of exclusive user testing, Daydream has now made the chatbot openly available through a public beta program. Upon registering, users provide details such as name, birthdate, preferred price range, and brand likes, enabling personalized experiences from the outset.
Shoppers can interact with the chatbot by using natural-language prompts—such as requesting attire for specific occasions or events—or by uploading images along with descriptive context. Customers have the option to save items into personalized collections or refine their searches directly by providing further instructions to the AI assistant.
The Daydream app employs an innovative function called the “Say More” option, through which users can request adjustments to items they like, such as alternative styles or different color variations, allowing greater customization. Utilizing data gathered during onboarding and continuous feedback from users, Daydream generates a unique “style passport,” offering tailored fashion recommendations. The system also presents daily curated fashion inspiration to keep users engaged and consistently discover fresh styling ideas.
Currently, Daydream does not handle direct transactions. Users interested in purchasing items are redirected to external merchant websites, and Daydream takes a percentage of each resulting sale as its revenue model. At launch, the platform boasts partnerships with over 8,000 brands, all onboarded free of charge to encourage merchant participation.
Bornstein, whose extensive background includes leadership roles at notable brands such as Nordstrom, Urban Outfitters, Sephora, and Stitch Fix, emphasized that Daydream spent considerable time over the past year building the infrastructure and refining AI technologies to greatly improve traditional search experiences. “Search has always been somewhat neglected in e-commerce,” she stated, explaining the limitations that have defined traditional methods. “Historically, consumers have adapted their searches to short, specific phrases like ‘red dress,’ but recent advances with chat-based AI like ChatGPT have trained customers to articulate more detail-rich queries.”
CTO Maria Belousova, who joined Daydream earlier this year, highlighted the advancements made by the team to better understand subtle attributes of inventory items—such as silhouette, embellishments, and even contextual scenarios like weddings or events. She noted that traditional methods relying solely on tags are insufficient for contemporary customers who articulate complex queries. Daydream thus leverages visual recognition technology to interpret product images more effectively and deliver precise results.
In addition to its current capabilities, the company plans to implement more explicit feedback mechanisms for users, such as requests to exclude certain attributes entirely—for example, “Don’t show me any four-inch heels.” Daydream is considering additional features like personalized suggestions that match with items already owned by users, expanded social sharing options, and the ability to adapt collections shared by other users to personal preferences using AI tools.
Daydream faces competition from startups like Deft and Cherry, which also focus on AI-driven shopping experiences. At the same time, technology giants like Amazon and Google are making similar strides with AI-powered product discovery and enhanced shopping solutions.
