Every time you walk through a crowded tourist spot or attend a stadium concert, you become an extra in someone else's digital memory.
There is a massive, invisible digital footprint of your face scattered across the internet. There are likely thousands of photos of you sitting on servers right now that you will never know about. It begs a fascinating question: How cool would it be to find them?
Imagine being able to query the entire internet for your own face to find that random background shot of yourself in New York from 2018. But to build a tool that searches the open web for your face, a company has to relentlessly scrape billions of images without permission. It requires strip-mining personal data and violating privacy just to satisfy a curiosity.
I wanted to explore the technical side of facial matching without the shady data practices. That is why I built DopplGrid.
DopplGrid is a closed-loop, 100% private facial recognition network. Instead of scraping the open web, it operates as a secure vault. Our database only grows when real people explicitly choose to opt-in and lock their faces into the grid.
