This company provides an AI-powered personal shopping agent for fashion discovery across thousands of online stores. Users chat with the agent to shop for personalized recommendations in both women's and men's apparel. It streamlines the e-commerce experience by offering curated product discovery based on individual preferences.
Funding
$49.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
FFounders
Product
Problem
Finding specific clothing items online, such as particular styles or materials, can be time-consuming and inefficient due to the vast and often poorly categorized inventory across e-commerce platforms. Current search methods often fail to accurately capture nuanced preferences, leading to irrelevant results and a frustrating user experience.
Solution
Daydream employs generative AI, machine learning, and computer vision to provide personalized shopping results tailored to individual preferences. The platform analyzes user input, such as text descriptions or visual examples, to understand the desired clothing item's attributes, including style, material, color, and other relevant features. By leveraging these technologies, Daydream streamlines the search process, filters out irrelevant options, and presents users with a curated selection of clothing items that closely match their specific needs. This approach enhances the user experience by reducing search time and increasing the likelihood of finding the perfect item.
Target Audience
Daydream primarily targets online shoppers who are looking for specific or niche clothing items and desire a more efficient and personalized search experience.
Features
- Generative AI-powered search engine that interprets natural language descriptions of clothing items.
- Machine learning algorithms that learn user preferences and refine search results over time.
- Computer vision technology that analyzes visual examples to identify desired attributes.
- Personalized recommendations based on individual style profiles and past searches.
- Real-time filtering and sorting options to narrow down results based on specific criteria.