About Face Privacy

We build the expertise that finds your face, so we can help you take it back.

Over a decade in facial recognition

We've been building and working on facial recognition technology for over a decade, with TensorFlow, earlier machine learning and AI models, and the tools that power real-world tracking and identification.

Our stack has included object and face detection frameworks such as YOLO, OpenCV, dlib, MTCNN, and face_recognition, as well as custom pipelines on TensorFlow and other frameworks. We understand how faces are detected, matched, and stored across systems.

We're constantly keeping up to date with who builds the next model, database, or service, so we can stay one step ahead and uphold users' privacy. When new players or technologies emerge, we adapt our processes to help you remain as private as you want to be.

Our mission

To try to help users become more private. We understand that some people like to be private, and in a world of facial recognition and public databases, that choice should be respected. We aim to give people tools and options to reduce their exposure and protect their face data where the law and industry allow.