Dresscoder: AI-Powered Fashion Search Platform
The Challenge
Dresscoder (Sravnuk.ru) needed technical consulting to build an intelligent fashion search platform that could help users find clothing items by photo and discover cheaper alternatives. The platform required advanced computer vision capabilities and a scalable architecture to handle image processing and price comparison across multiple retailers.
My Role
My Role: Strategic planning, team building and hiring, architecture design, technical leadership.
The Solution
We provided comprehensive technical consulting services:
- Technology Stack Recommendation: Advised on using modern AI/ML frameworks for computer vision and deep learning fashion understanding
- Architecture Design: Designed a scalable microservices architecture to handle image processing, search, and price comparison
- Team Building: Helped recruit and interview ML engineers and backend developers specializing in computer vision
- Technical Roadmap: Created a detailed technical implementation plan for MVP and future scaling
Key Features Implemented
- Visual Search: Search for clothing by uploading photos or taking pictures in stores
- Price Comparison: Find similar items at better prices across multiple retailers
- Style Recommendations: AI-powered outfit suggestions based on uploaded items
- Wardrobe Matching: Help users create complete looks with items from their personal wardrobe
Results
- Successfully launched the platform with AI-powered visual search capabilities
- Built a team of 5 engineers including ML specialists and backend developers
- Implemented a scalable architecture handling thousands of image searches daily
- Established partnerships with major fashion retailers for price comparison
Technologies Consulted On
- AI/ML: TensorFlow, PyTorch for computer vision models
- Backend: Python, FastAPI for high-performance APIs
- Infrastructure: AWS/GCP for scalable cloud deployment
- Search: Elasticsearch with vector similarity search