PureLens

Inspiration

Like many people, I’ve often stood in a store aisle staring at a product label, feeling completely overwhelmed. Whether it’s a skincare serum, a snack for my family, or a new medicine, the ingredients are usually a wall of unreadable chemical names. I wanted to create a tool that cuts through the marketing hype and gives users the "truth" about what they are putting on or in their bodies. PureLens was born from the desire to make professional-grade health intelligence accessible to everyone with a smartphone.

What it does

AI-powered health guardian that deciphers complex product labels in seconds. Multimodal Scanning: Users scan a product's ingredient list using their camera. Instant Reasoning: Powered by Gemini 3, the app doesn't just look up a database; it "reasons" through the chemical compounds to identify irritants, toxins, or beneficial nutrients. Safety Scoring: It generates a Body-Safety Score (0-100) personalized to the user's health profile (e.g., sensitive skin, nut allergies). Community Wisdom: It integrates a social rating system where users share real-world experiences, helping others see if a product actually works or causes adverse reactions.

How we built it

We leveraged the cutting-edge capabilities of the Gemini 3 API to handle the heavy lifting in google ai studio

Challenges we ran into

One of the most significant challenges we faced was not technical, but infrastructural. To ensure the app could handle high-traffic scanning, we attempted to upgrade to a production-grade Google Cloud Billing account on February 7th. However, we encountered a delay in the banking verification process; the GOOGLE*MDZ verification code required to activate the billing account did not arrive in our bank statement in time for the final deployment. This meant we had to pivot our deployment strategy. Because the API key functionality was limited by the inactive billing status on Netlify, we had to optimize our code to run within the Free Tier constraints and rely on local environment testing to prove the full agentic reasoning capabilities of Gemini 3.

Accomplishments that we're proud of

As someone with no prior background in software development, my biggest accomplishment is simply that the app worked. Coming into this hackathon, I had a vision but i thaught i would be difficult. I am incredibly proud of: Turning an Idea into Reality: Gemini 3 acted as a true collaborator. It understood my vision for a health-conscious scanner and translated my thoughts into a functioning product. Seamless Debugging: Whenever I ran into a "bug" or a technical wall, I simply explained the problem to the model. It diagnosed the issue and corrected the code instantly. I expected this process to be frustrating like the other model, but it was actually enjoyable. the synergy between my creative intent and the model's technical execution allowed me to focus on the user experience and the health mission rather than getting stuck in syntax. Building a Full-Stack Solution: In just 6 days, I went from an idea to a working product with AI vision, reasoning, and a community framework that is cool