Daydream AI chatbot for fashion shopping debuts with personalized flair
Finding the perfect outfit just got smarter with Daydream AI chatbot for fashion shopping. Shoppers looking for a more intuitive, customized, and visually engaging experience can now explore their fashion preferences through natural language or image-based queries. Created by Julie Bornstein, a retail industry veteran, the chatbot is now available to the public in beta—offering a glimpse into the future of how we search, shop, and style ourselves using artificial intelligence. With over 8,000 brands on the platform, users can get curated suggestions, build style collections, and even refine results based on their evolving preferences.
The platform uses onboarding data like name, birthday, brand interests, and budget to personalize recommendations. Whether you want a dress for a summer wedding in Paris or are hunting for a jacket inspired by an Instagram post, the chatbot delivers options that closely match your intent. Daydream is designed to be more than a shopping assistant—it's a smart fashion companion tailored to your aesthetic. Let’s break down how this AI fashion tool works and what makes it stand out.
How Daydream AI chatbot for fashion shopping works
The Daydream AI chatbot for fashion shopping starts by asking for basic but useful inputs—such as your name, birthdate, spending preferences, and favorite brands. This onboarding process isn’t just for show; it powers your “style passport,” a dynamic profile that the chatbot uses to refine your shopping experience. Users can type detailed prompts like “a business-casual blazer for fall in New York” or simply upload an image of something they like. The system combines these cues with natural language understanding to deliver accurate, stylish results.
What sets Daydream apart is its ability to tweak and learn. Users can click the "Say More" button next to any suggestion to modify colors, cuts, or styles, making it easy to hone in on exactly what you’re looking for. Unlike traditional e-commerce sites where filters feel rigid, this AI-driven interface adapts to subtle user preferences. Over time, it becomes better at surfacing items that align with your taste, making each session more relevant than the last. And since it updates daily with new inspiration, it feels less like browsing a catalog and more like discovering your next favorite look.
Fashion meets personalization through AI
Shopping for clothes often feels overwhelming due to the sheer number of choices. That’s exactly the problem the Daydream AI chatbot for fashion shopping solves. Rather than endlessly scrolling through pages of irrelevant products, users get curated looks that reflect their preferences. This personalized approach creates a smoother experience for fashion discovery, especially for shoppers who don’t have time—or patience—for traditional browsing.
The chatbot also organizes saved items into collections, allowing users to plan their wardrobe, create mood boards, or just keep a wishlist for future purchases. The real-time interactivity means you can keep refining your style journey without starting over. Even though checkout currently redirects users to merchant websites, the process is still fluid and user-friendly. With no need to search across different platforms, Daydream acts like a centralized AI fashion hub that connects people with what they actually want to wear.
Julie Bornstein’s vision: Redefining fashion e-commerce
Julie Bornstein’s experience at Nordstrom, Sephora, Urban Outfitters, and Stitch Fix heavily influences Daydream’s focus on personalization and technology. Her goal was to unify multiple brand catalogs into one intuitive shopping destination powered by AI. After a successful $50 million seed round, Daydream has spent the last year building backend technology that not only surfaces product listings but understands context, mood, and user intent.
The decision to launch without an integrated checkout flow was strategic—it allows Daydream to partner freely with merchants while taking a small cut from completed sales. The platform already boasts over 8,000 brands and is onboarding more at no cost. This openness encourages fashion houses of all sizes to join, giving users access to both established and emerging labels. For shoppers, that means more variety, and for retailers, it means visibility in an AI-powered environment designed to boost conversion through hyper-relevant recommendations.
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