PetsyDNA

Goals and Objectives of the Mobile App

The goal of the project was to create a convenient, functional, and visually appealing interface for identifying pet breeds from photos. The app analyzes images using artificial intelligence and determines the breed with high accuracy. It is useful for both pet owners and volunteers working in shelters or identifying animals on the street.

• Scan the animal via camera or upload a photo from the gallery.
• Automatic breed recognition using artificial intelligence.
• Display of results with probability percentage and a short description.
• Option to create a profile for the pet.
• Intuitive interface with smooth navigation.

Development Technologies

The app architecture is based on a client-server model with secure API communication. React Native was used for cross-platform development, and the design was created in Figma following Material Design and Human Interface Guidelines principles. Machine learning ensures accurate breed recognition from images.

• Frontend: React Native (iOS + Android).
• Backend: Node.js, database, API integrations.
• UI/UX: Figma, wireframing, prototype testing.
• AI model and open APIs for image recognition.

App Functionality

For Users:

• Scan or upload a photo of the animal.
• Instant breed recognition with result display.
• Breed information: price, characteristics, historical background.
• Ability to add a pet profile with photo, weight, age, etc.

For Business:

• Flexible architecture with scalability potential.
• Cross-platform compatibility with a unified codebase.
• Cost optimization for development and maintenance.
• Ability to add new features and adapt to market needs.

Project Outcomes

The app has become an effective tool for pet owners, volunteers, and veterinarians. With accurate breed recognition, an intuitive interface, and modern architecture, it combines artificial intelligence technology with ease of use. This has led to positive user feedback and readiness for international market scaling.