Inspiration

Lost-pet posts often spread incomplete information, while people are understandably cautious about sharing exact addresses or handing an animal to the wrong person. PawLink explores a safer first step: structured, approximate details with a transparent explanation for every possible match.

What it does

PawLink compares a lost-pet or found-pet report with a small synthetic community board. It uses species, size, coat color, approximate neighborhood, and distinctive markings to rank possible leads. Every result shows the matching signals and a safe next action. The interface repeatedly reminds users that a match is not proof of ownership and requires human verification.

How we built it

This is a single-page HTML, CSS, and JavaScript prototype with no external API or account dependency. A deterministic weighted scoring function makes the demo reproducible and auditable. Synthetic reports are embedded locally so no real person, address, or animal image is exposed. The app is deployed as a public GitHub Pages site.

Humane safeguards

PawLink intentionally avoids facial-recognition claims. It uses approximate locations instead of home addresses and recommends shelter or campus-security verification, private proof, and safe handover steps. It is a coordination aid, not an animal registry or a substitute for professional welfare support.

Challenges and learnings

The hardest design choice was balancing usefulness with the risk of false matches. Showing the signals behind a score makes uncertainty visible and keeps the decision with a human. A production version would need consent-based shelter partnerships, moderation, secure messaging, audit logs, and carefully tested welfare escalation protocols.

Built for AnimalHack

PawLink is a new, event-specific prototype focused on lost-pet reunification and responsible human-animal relationships. The current demo uses synthetic data and makes no claim of real-world reunifications.

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