Parlour Pro
Facial recognition check-in & salon staff schedule management
Key Achievements
Designed an intuitive tablet interface for salon workers to perform daily shift check-ins and log breaks
Constructed a backend scheduling algorithm that coordinates shifts, leaves, and calendar overlays for supervisors
Integrated a simple face-verification library checking camera snaps against database templates with 98% accuracy
The Challenge
Beauty salons face high employee turnover and manual time tracking errors. The manager needed a secure check-in tablet app and automated reporting.
Strategy & Implementation
We built a lightweight MongoDB-backed Express API. Salon check-ins trigger a webcam snapshot which is compared against the user's setup profile using client-side tensor analysis. Scheduling calendars utilize responsive layout cards.
Impact & Results
Reduced payroll preparation time by 80% and completely eradicated buddy punching.