Needemand’s BorderAge solution offers a compelling example of a non-facial, privacy-preserving age estimation modality. Unlike most Trial participants, Needemand does not rely on facial analysis, voice or any biometric traits traditionally associated with identity. Instead, it uses hand gesture dynamics, captured via a device’s camera, to whether a user is likely an adult or a child.
Fast and lightweight, Needemand’s system is ideal for constrained devices or physical environments like kiosks or mobile retail setups.
Enables inclusive access by avoiding biases linked to facial recognition; useful in contexts where users decline image-based processing.
Needemand’s gesture-based system proved lightweight, privacy-preserving and effective for simple age gates. It offers an innovative alternative to facial AI, suitable for specific contexts with low biometric tolerance.