On July 29, 2026, Daydream, the AI-powered fashion search and discovery platform, launched Powered by Daydream, bringing natural-language product search directly onto fashion retailers' own websites. Shoppers can now describe what they want in plain language instead of clicking through filters and keyword fields.
That is a real fix for a real problem. But finding the right product was never fashion ecommerce's biggest obstacle. Deciding to buy it is.
What Did Daydream Just Launch?
Daydream launched a B2B version of its AI search technology, letting fashion brands embed natural-language, conversational product discovery directly on their own sites rather than sending shoppers to a separate app.
STAUD, Alice + Olivia, Couper, Cult Mia, and Hampden Clothing are live in the initial pilot, with more than 25 additional retailers signed on, including Anine Bing, Mansur Gavriel, Sandro, and Maje.
"Search has never been a strong suit on most fashion sites," said Julie Bornstein, Founder and CEO of Daydream. "It has traditionally been keyword-based and tied to each site's taxonomy, which often doesn't reflect the language customers actually use."
The launch follows a strong first year. Daydream has surpassed 1.5 million shoppers, with a catalog spanning 325 retailers, more than 10,000 brands, and 3 million products.
Why Doesn't Better Search Alone Solve Fashion Ecommerce's Conversion Problem?
Better search alone does not solve fashion ecommerce's conversion problem because finding a product and trusting a purchase decision are two different tasks. Average ecommerce conversion rates are stalling at just 1.65%, according to DRESSX's own 2026 Virtual Try-On Report, even as search and recommendation technology keeps improving.
Fashion carries a specific version of this gap. A shopper can describe exactly what they want and still hesitate, because they cannot physically try the product on before buying. Online apparel return rates still run between 30% and 40% industry-wide, largely because of that same uncertainty.
DRESSX has covered that pattern in more detail in how virtual try-on helps fashion brands reduce returns.
Natural language search removes the friction of finding a product. It does nothing to resolve whether that product is actually right for the shopper who found it.
What Does the Data Show About Confidence and Conversion?
DRESSX Intelligence analyzed shopping behavior across more than 1.2 million shoppers and found that confidence, not discovery, is what moves a shopper from browsing to buying.
Shoppers who used AI Virtual Try-On were 50% more likely to purchase than shoppers who did not use it, and added items to cart at roughly 3 times the rate. They also viewed 7 times as many products before deciding, a sign of exploration rather than hesitation once uncertainty is resolved.
Engagement carried well past the first purchase. 44% of virtual try-on users remained actively engaged with a brand through Day 30, compared with the steep drop-off most ecommerce sites see after a shopper's first visit.
Daria Shapovalova and Natalia Modenova, co-founders of DRESSX, framed the shift directly: "Natural language search is a major step forward because it removes friction from product discovery."
"But the hardest part is helping customers feel confident enough to buy," they said. "AI search and Virtual Try-On solve different problems, and together they create a much more complete shopping experience."
How Discovery and Confidence Work Together in Practice
DRESSX, the AI fashion commerce company that has built virtual try-on and AI shopping technology for brands since 2020, already runs both sides of this equation for one retailer.
At Windsor, conversational AI search and AI Virtual Try-On are both powered by DRESSX. Shoppers describe what they are looking for in natural language, then instantly see the recommended pieces visualized on themselves before adding anything to cart.
That pairing turns discovery and confidence into two layers of the same journey, instead of two separate tools a shopper has to reconcile on their own.
DRESSX has covered this kind of AI-powered discovery and personalization in more detail, including how it applies across chat and CRM.
The founders' broader point is that no single AI capability will define fashion ecommerce's next phase. Retailers are more likely to combine multiple AI technologies across the shopping journey than to rely on any single breakthrough.
What This Means for Fashion Ecommerce Leaders
A few questions can clarify where a brand's AI stack has a gap, beyond whichever tool made headlines most recently.
Does your search solve discovery, evaluation, or both? Natural language search narrows a catalog. It does not tell a shopper whether a specific piece will fit or suit them.
Where does hesitation show up after a shopper finds the right product? Cart abandonment after a successful search points to a confidence problem, not a discovery one.
Are your AI investments covering the full journey? Discovery and visualization each address a different stage, and skipping either one leaves a gap the rest of the stack cannot close.
What does your return rate say about fit and appearance confidence? A return rate near the 30% to 40% industry range suggests shoppers are still guessing after they buy, not before.
Discovery Gets Shoppers to the Product. Confidence Gets Them to Checkout.
Daydream's launch is a genuine step forward for how shoppers find fashion products online. It also sharpens a question the industry has not fully answered: what happens after a shopper finds exactly what they were looking for.
DRESSX Virtual Try-On was built to answer that question, giving shoppers the confidence to act on what better search already helped them discover.
