HairHaven
A unified barber management platform with AI-powered hairstyle recommendations, appointment scheduling, and retrieval-augmented client history.
The Challenge
Barbers face a common problem: clients often struggle to communicate what hairstyle they want, leading to longer consultations and sometimes disappointing results.
Traditional booking systems don't capture client preferences, style history, or help with the discovery process. Each visit feels like starting from scratch.
Constraints
- Real-time recommendations during consultations
- Mobile-first for in-shop use
- Integration with existing booking workflows
- Privacy-conscious handling of client photos
- Offline capability for areas with poor connectivity
Solution Architecture
Implementation Details
Face Shape Analysis
CNN-based classifier trained on facial landmark data to identify face shapes (oval, round, square, etc.) and recommend complementary styles.
Style Matching
CLIP-based embedding model to encode hairstyle images. Vector similarity search to find styles that match client preferences and face shape.
Client History RAG
Retrieval-augmented system that surfaces past preferences, notes from previous visits, and successful style choices.
Real-time Inference
Optimized inference pipeline with model quantization for sub-200ms recommendations on mobile devices.
Results
60%
Reduction in consultation time
<200ms
Recommendation latency
89%
Client satisfaction with suggestions
The platform shipped with full production infrastructure including monitoring, error tracking, and A/B testing capabilities. The recommendation system continues to improve as more client feedback is collected.