Animal Care

The Animal Care logo — representing our mission to make pet care smarter, simpler, and more accessible through AI

Inspiration

We created AnimalCare because many pet owners struggle to understand whether a symptom is serious, what might be causing it, and what they should do next. Access to professional veterinary care is not always immediate or affordable, especially when an owner needs quick guidance.

Our goal was to build a simple tool that uses AI to provide helpful preliminary guidance while encouraging responsible veterinary care when professional attention is needed.

What We Built

AnimalCare is an AI-powered pet care assistant. Users can describe their pet's symptoms or condition, and the system analyzes the information and provides an easy-to-understand response, including possible concerns, recommended actions, and guidance on when veterinary attention may be necessary.

We focused on making the interface simple and accessible so that users can quickly provide information and understand the AI's response.

How We Built It

The project consists of a React Native + Expo frontend and a FastAPI backend.

The frontend provides the user interface and communicates with the backend through an API. The backend processes the user's input and integrates Google Gemini to generate the AI-powered analysis and recommendations.

The web version was deployed using Cloudflare Pages, while the FastAPI backend was deployed using FastAPI Cloud.

What We Learned

During development, we learned how to connect a React Native/Expo application with a production FastAPI backend, configure environment variables for deployed services, integrate a generative AI model into an application, and deploy both frontend and backend independently.

We also learned that building an AI application is not only about getting a model to generate an answer. Designing the right input, structuring the response, handling errors, and creating a simple user experience are equally important.

Challenges We Faced

One of our main challenges was moving the project from a local development environment to a real production environment. This required solving issues related to API connectivity, environment variables, deployment configuration, and static assets.

Another challenge was making AI-generated information useful without presenting it as a definitive veterinary diagnosis. We designed AnimalCare as a supportive guidance tool, rather than a replacement for professional veterinary care.

Despite these challenges, building AnimalCare gave us practical experience in developing, integrating, and deploying a complete AI-powered application from frontend to backend.