This is a submission for Weekend Challenge: Dog Days Edition
What I Built
PawGuard is a community web platform built to help protect dogs from abuse, severe neglect, and abandonment. When someone spots a dog in danger—whether chained without water, hit by a car, or dumped—they can submit a report in seconds with their GPS location, photos, urgency level, and even stay anonymous if needed. Those alerts are routed directly to local rescue contacts and volunteers via WhatsApp and email so someone can respond quickly.
In addition to emergency reports, the platform includes a noticeboard for lost and found pets (with instant printable flyers), an adoption and foster board, and practical guides on animal welfare.
My main goal with PawGuard was to remove the friction between seeing an animal suffering on the street and actually getting help to them. Too often, people don't know who to call or where to report neglect. PawGuard gives everyday people a direct, fast way to speak up and connects them with volunteers who can step in.
Demo
https://paw-guard-two.vercel.app
Code
https://github.com/comzzy-comzzy/PawGuard
How I Built It
I built PawGuard as a responsive single-page web application using React 18, TypeScript, and Vite, styled with Tailwind CSS and custom CSS animation keyframes.
A few key technical decisions shaped the build:
Zero-Delay Emergency Dispatch: Instead of locking emergency reports behind authentication or waiting on slow backend pipelines, I built client-side triage and routing that immediately bundles report details (GPS coordinates, urgency classification, incident notes) into structured WhatsApp and email dispatch links. Rescuers get the exact location and photos sent directly to their phones in real time.
Dynamic Audio & Custom Animations: Animal rescue platforms can often feel bleak and heavy. I used the Web Audio API for lightweight synthesized sound effects and custom keyframe animations for our canine mascots, creating an engaging, welcoming experience without bloating page load times.
Instant Printable Flyer Generation: For lost and abandoned dogs, we implemented client-side flyer generation directly in the browser so community members can print or share high-visibility search notices immediately.
Guided Intake Companion ("Picky"): I implemented an interactive conversation flow that walks stressed witnesses step-by-step through capturing the essential details needed for a rescue (exact landmarks, condition of the dog, immediate threats).
Best Use of Google AI — Antigravity with Gemini 3.7 (High Reasoning)
I leveraged Google Antigravity powered by Gemini 3.7 (High reasoning mode) as our core development and architectural copilot throughout the project.
With Gemini 3.7's deep multi-step reasoning:
• I architected resilient state flows for complex multi-module forms (abuse intake, foster applications, and lost pet postings).
• I rapidly designed and refined the interactive triage logic and geolocation fallbacks, ensuring reports are formatted accurately even when network conditions or location services are spotty.
• Antigravity helped me implement clean, fully typed TypeScript schemas and custom UI micro-interactions, cutting development time drastically while keeping the codebase modular and maintainable.
Prize Categories
Best Use of Google AI.
Team Submissions: Hi I'm a Solobuilder i havent added anyone yet to my team
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