LayR
The ultimate AI stylist and digital closet. Discover, create, and plan outfits from what you own — wear more, buy better, and waste less.
- Digitize your wardrobe in minutes
Simply snap photos of your clothes and our AI automatically categorizes everything by type, color, and style - AI-generated outfits from what you own
Get personalized outfit combinations based on weather, occasion, and your unique style preferences - Smarter shopping, with your closet in your hand
See what you already own before buying, discover gaps in your wardrobe, and make informed purchase decisions
About LayR
LayR is revolutionizing how people interact with their wardrobes through AI-powered styling and digital closet management.
What We Do
LayR transforms the way people manage their wardrobes by digitizing clothing collections and providing AI-powered styling recommendations.
Our platform helps users make better fashion decisions, reduce waste, and maximize the potential of their existing wardrobe.
We combine computer vision, machine learning, and fashion expertise to create personalized outfit suggestions that match individual style preferences, weather conditions, and occasions.
Problems We Solve
Decision Fatigue: Eliminate the daily stress of choosing what to wear by providing instant, personalized outfit recommendations.
Wardrobe Inefficiency: Help users rediscover and maximize their existing clothes through AI-powered categorization.
Sustainable Fashion: Reduce overconsumption and fashion waste by encouraging smarter shopping decisions.
Target Audience
Our primary users are Gen Z professionals and fashion enthusiasts aged 18-35 who value sustainability, efficiency, and personal style.
These users are tech-savvy individuals who appreciate personalized experiences that save time while enhancing their personal style and environmental consciousness.
They're looking for smarter ways to manage their wardrobes, make confident fashion choices, and reduce their environmental footprint without compromising on style.
Industry Context
The global fashion industry generates over $2.5 trillion annually, yet the average person only wears 20% of their wardrobe regularly. With growing awareness of fashion's environmental impact and the rise of AI technology, there's unprecedented opportunity to create solutions that promote sustainable fashion consumption while enhancing personal style.
Products & Services
LayR offers a comprehensive AI-powered wardrobe management platform with the following core features:
Digital Wardrobe
Upload and automatically categorize your clothing items using computer vision. Our AI identifies colors, patterns, styles, and clothing types to build your digital closet.
AI Outfit Generation
Get personalized outfit suggestions based on your style preferences, weather conditions, and occasion. Our AI learns from your choices to improve recommendations over time.
Style Profile
Build a comprehensive style profile that captures your preferences, lifestyle, and fashion goals. The more you use LayR, the better it understands your unique style.
Styling Tips
Receive personalized styling advice and fashion tips tailored to your body type, lifestyle, and preferences. Learn how to mix and match your existing pieces effectively.
Smarter Personalised Shopping
Make informed purchase decisions with AI-powered shopping recommendations that complement your existing wardrobe and fill identified gaps in your style collection.
Virtual Try On
Visualize how different outfits will look on you before getting dressed. Our AR technology helps you experiment with combinations and see yourself in new styles.
Team
Meet the founder building the future of AI-powered fashion technology
Uday Khanna
Founder & CEO
Machine Learning Engineer with 5+ years of experience in AI/ML, specializing in NLP and LLM agents for building intelligent recommendation and search systems.
Previously worked as a Machine Learning Engineer at Atlassian, where he built and scaled recommendation engines that served millions of users, with deep expertise in personalization algorithms and user behavior analysis.
Passionate about sustainable fashion and leveraging AI to solve real-world problems in the fashion industry.
Key Achievements at Atlassian
Improved Customer Satisfaction: Enhanced search systems from 15% to 60% CSAT through advanced reranker models and query reformulation techniques
Performance Optimization: Reduced query latency by 2.5 seconds through binary embeddings migration and Hamming distance similarity search
System Architecture: Designed end-to-end embedding migration pipelines with minimal downtime and seamless infrastructure integration
Evaluation Framework: Established robust LLM-based evaluation systems with human-in-the-loop for high-fidelity assessment of ML pipelines