05 / CARE IN MOTION
CatCare
A nutrition recommendation system built for foster cats that combines personalized machine learning with nutritional standards.
I built CatCare because I couldn’t find a reliable, science-backed way to figure out what my foster cats should actually be eating. Most recommendations online are vague, brand-sponsored, or don’t account for a cat’s individual needs. So I built something that does.
CatCare combines neural collaborative filtering with AAFCO nutritional compliance standards to generate personalized food recommendations for cats.
01 / PROFILE
Start with the cat.
Enter a cat’s age, weight, health considerations, and other essentials. CatCare turns that individual profile into a nutrition-aware starting point.
02 / RECOMMEND
Learn, then verify.
The model learns preference patterns while a compliance layer checks each recommendation against AAFCO thresholds — personalization with a nutritional floor.
03 / TOOLKIT
Built to travel.
PyTorch · FastAPI · React · MLflow · Railway
04 / PRODUCT VIEWS
05 / WHAT’S NEXT
CatCare is a starting point. The long-term vision is a tool shelters can use to manage nutrition across large populations of cats with varying needs, and that individual owners can trust when they need real answers, not guesswork.