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Orvy

Orvy

Facial recognition and emotion detection to revolutionize daycare management.

Industry

Education

Services

Computer Vision, App Development

Timeline

8 months

Year

2024

The Challenge01

Daycares trapped in manual processes

Kindergartens and daycares face enormous operational challenges: manual attendance tracking, inefficient parent communication, lack of visibility into children's emotional wellbeing, paper-based reports, and complicated payment and billing management.

iOS app — parent view at KinderArcoiris. Dashboard with 5 modules: Pickup Now, Daily Reports, Announcements, Chat and My Family. Nav: Calendar, Finances, Menu, Chat, More
01

iOS app — parent view at KinderArcoiris. Dashboard with 5 modules: Pickup Now, Daily Reports, Announcements, Chat and My Family. Nav: Calendar, Finances, Menu, Chat, More

Executive dashboard — KinderEstrella, 191 active students, 7 published events, 764 pending documents. Modules: Pickup Now, Families, Tutors
02

Executive dashboard — KinderEstrella, 191 active students, 7 published events, 764 pending documents. Modules: Pickup Now, Families, Tutors

The Solution02

A complete AI-powered platform

We created Orvy, a complete platform that includes facial recognition with real-time emotion detection, ALPR system for vehicle check-in/check-out, automated digital daily reports with photos and videos, educator dashboard, developmental milestone tracking, secure parent-teacher messaging, payment and billing management, and individual and group progress metrics.

Student directory — full grid with real names, groups (Preschool 1A/1B/1C, Maternal) and avatars. Filters: Families, Students, Tutors, Employees
01

Student directory — full grid with real names, groups (Preschool 1A/1B/1C, Maternal) and avatars. Filters: Families, Students, Tutors, Employees

Roll Call Record — real-time attendance. Maternal A with 18 students, In/Out indicators and search by name or classroom
02

Roll Call Record — real-time attendance. Maternal A with 18 students, In/Out indicators and search by name or classroom

The Process03

Rapid prototyping and field testing

We started with facial recognition prototypes using TensorFlow Lite, tested directly in daycares. We iterated on the educator dashboard with feedback from real teachers, and built the daily report system in collaboration with parents.

Access Control — facial recognition camera activating. "Starting camera... Please wait." Automatic check-in/check-out via facial recognition
01

Access Control — facial recognition camera activating. "Starting camera... Please wait." Automatic check-in/check-out via facial recognition

The Results

Numbers that matter

98%

Recognition accuracy

Real-time

Emotion analysis

85%

Engagement increase

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