Refy9 offers a fashion platform that combines personal styling with community-driven inspiration, helping users make outfit decisions by remembering their closet, occasion, budget, weather, and community context. The platform's AI companion, Okkai, learns user preferences over time to deliver increasingly personalized recommendations. It also provides a dedicated community space where users can share looks, get feedback, and style together.
Funding
Funding not disclosed
Founders
Product
Problem
Fashion decisions are difficult not because of clothes themselves, but because of the overwhelming amount of context people must remember—occasion, budget, weather, and community input. Users often struggle to recall what they own, what fits the moment, and what their social circle would approve of, leading to decision fatigue and guesswork when getting ready.
Solution
Refy9 provides a fashion platform that acts as a personal styling companion, helping users unlock their closet and make confident outfit choices. The platform's AI-driven assistant, Okkai, learns from user interactions over time to understand individual preferences, lifestyle, and context, delivering recommendations that improve with each use. Users can share looks, get inspired, and style together within a built-in community, transforming fashion from a solitary decision into a collaborative experience. The platform prioritizes understanding before recommending, remembering before selling, and community before commerce, ensuring the technology serves the user's personal style rather than pushing products.
Target Audience
Primary users are fashion-conscious individuals who want personalized styling assistance and social inspiration, as well as style communities seeking a collaborative platform for sharing looks and getting feedback.
Features
- AI-powered personal stylist (Okkai) that learns user preferences and lifestyle context over time for increasingly accurate recommendations
- Closet management system that remembers owned items and suggests combinations based on occasion, budget, and weather
- Community feature where users can share looks, ask for feedback, and co-style with friends or followers
- Context-aware recommendation engine that factors in occasion, budget, weather, and community input
- User-centric design philosophy that prioritizes understanding and remembering over selling, with a "Become Before Consume" approach