Dog onboarding
Collects identity, personality, and photo inputs so the companion starts from a specific real pet rather than a generic mascot.
ProjectBuilding
Project profile
Pawprint
A mobile AI companion prototype that turns a real dog into a warm digital twin.
Pawprint explores the space between pet care, companionship, and lightweight AI personalization: a digital twin should feel emotionally present without pretending to replace the real relationship.
Building
Status
Registry state
The loneliness economy and pet humanization
Profile
Macro tailwind
2026-05-28
Updated
Public build log
What it is
An Expo Go-first mobile app for onboarding a real dog, generating a stylized avatar, and giving the owner a simple care-and-bond loop they can revisit on their phone.
The loneliness economy and pet humanization
Loneliness has become a global public-health and consumer-behavior theme, while pet ownership remains resilient and emotionally central for many households. Pawprint sits at that intersection: companion technology anchored in a real animal bond.
Core functionality
Avatar generation
Uses a local/provider-ready backend boundary so AI image generation can be tested without placing keys inside the mobile bundle.
Companion home
Shows a centered avatar, bond progress, care actions, reminders, and recoverable mood changes.
Local persistence
Stores the dog profile and care state locally so the prototype can run quickly through Expo Go.
Architecture
The build keeps the mobile app and avatar-generation backend separated. Expo handles the phone experience; a local Node service handles provider-facing avatar generation and returns image assets to the app.
Stack
- Expo Router and React Native
- TypeScript app logic
- AsyncStorage for local persistence
- Expo notifications for reminders
- Local Node avatar server with provider-ready image pipeline
Data flow
- Owner creates a dog profile and answers identity questions.
- The app collects 3 to 5 dog photos for avatar input.
- A backend endpoint generates or falls back to a local procedural avatar.
- The app stores the resulting profile and powers a simple care loop.
Safeguards
- The app never calls AI providers directly from the mobile bundle.
- Local fallback keeps the prototype usable when generation is unavailable.
- Public copy should frame the product as companionship and care support, not therapy.
Customer and business lens
Wedge
Start with delight: a personalized dog twin that gives pet owners a reason to return before layering on care, commerce, or community.
Model
Potential models include premium avatar packs, care reminders, memory journals, pet wellness partnerships, or creator-style sharing loops.
Use cases
- Create a digital twin from photos and profile inputs.
- Check in on bond progress and care actions.
- Receive local reminders for simple routines.
- Use the avatar as a shareable emotional artifact.
Risks to watch
- The emotional tone must feel sincere rather than gimmicky.
- Avatar quality is a core trust and delight driver.
- Future AI or health features need stronger privacy and safety boundaries.
Personas
Solo pet parent
Uses the pet relationship as a major emotional anchor and wants a daily companion surface that feels personal.
Busy owner
Needs lightweight reminders and care nudges without a heavy pet-health management app.
Family sharer
Wants a playful digital version of the dog that family members can recognize, save, and share.
The pet-as-family owner
Treats the dog as a household member and responds to personalization, rituals, and memory keeping.
The lonely-city owner
Values the pet relationship as companionship and may appreciate a digital surface that extends that bond during the day.
The playful builder
Enjoys trying new AI tools and wants a charming artifact to show friends.
Progress kanban
Shipped
- Expo Go development loop
- Dog onboarding and identity questions
- Photo intake
- Local/provider-ready avatar generation
- Care actions, reminders, mood state, and persistence
In flight
- Avatar quality and rigging improvements
- Mobile visual polish
- Care loop tuning
Backlog
- Shared household profiles
- Memory/journal timeline
- Premium avatar styles
- Device build/TestFlight path
Visual evidence
Links and build receipts
Build receipts
- Local source signals include Expo routes, onboarding components, avatar renderer components, care engine services, reminders, and AsyncStorage-backed state.
- The current app is optimized for Expo Go preview rather than store distribution.