AI Pet Care App
We built a cross-platform pet care app for health, routines, and care history. It includes reminders, grooming schedules, multi-pet profiles, AI consultation, subscriptions, and pet matchmaking. It reached the Apple App Store in three weeks.
Anabulku had to unify pet-specific AI, health-record RAG, reminder schedules, multi-pet data isolation, subscriptions, and matchmaking. The AI creates reminders from chat. Reminder rules vary by vaccines, medication, grooming, and general care.
AI Pet Care App
The monorepo contains a NestJS API, an Expo/React Native app, and Next.js web surfaces. PostgreSQL stores users, pets, reminders, subscriptions, and health records. The API handles auth, persistence, subscriptions, scheduling, AI context, and tool execution. AI retrieves pet-specific data before answering. Cron jobs drive reminders, with caching and indexing on frequent records.
NestJS separated pets, reminders, AI, payments, matchmaking, and accounts. Expo and React Native shipped iOS and Android from one codebase. The monorepo keeps shared contracts and types aligned. The assistant retrieves data and performs care actions. Backend enforcement protects premium AI, pet limits, and paid features.
RAG grounds the assistant in pet profiles and health data. Backend tools create reminders. Cron scheduling covers vaccines, medication, grooming, and general care. Backend plan guards, PostgreSQL indexes, and caching protect hot paths. The same monorepo supports multi-pet context, matchmaking, and IAP subscriptions.
Released to the Apple App Store within three weeks.
Acquired first users within the first month.
Shipped an AI assistant grounded in pet-specific data that creates reminders.
Implemented multi-type reminders and multi-pet management.
Delivered in-app subscriptions with backend access control.
Established a modular core for continued product development.
AI grounded in structured product data.
Chat connected to backend actions such as reminder creation.
Reminder logic for multiple care types and recurrence patterns.
Data modeling across users, pets, reminders, subscriptions, and health records.
Cross-platform mobile delivery on a compressed timeline.
Consumer AI becomes useful when it connects user data to product workflows. It should manage care, not sit beside it as a separate chatbot.
Relevant to consumer mobile products with AI that works on user data. The approach fits healthcare, wellness, education, lifestyle, productivity, and vertical SaaS with reminders, records, subscriptions, and AI workflows.
We specialize in ai integration and mvp for consumer / pet care companies. If you're facing challenges like the ones we solved for Anabulku, let's talk.
