Shape Matrix™️

The Shape Matrix system uses geometric shapes to generate an inexhaustible number of visually appealing 2D and 3D marks – Shapetags – that serve as secure, serialized, hard-to-clone identifiers for physical and digital objects. Shapetags are easily recognized by the human eye, quickly authenticated with off-the-shelf mobile devices and impossible to decode without authorized access.

Introducing Shape Matrix

$13M from the world's leading tech investors

Our Investors

Bloomberg Beta

Box Group

GGV Capital

Greycroft

IA Ventures

Lerer Hippeau

Slow Ventures

Traverse Capital

Bloomberg Beta

Box Group

GGV Capital

Greycroft

IA Ventures

Lerer Hippeau

Slow Ventures

Traverse Capital

Testimonials

“Shape Matrix technology is a game changer for authentication and anti-counterfeiting. I have tested no other tag system that can embed its tags into 3D-printed parts and then ensure the veracity of the part through off-the-shelf scanning technologies. QR codes and barcodes are too difficult to include in 3D printed parts today given the resolution and scale of today’s commercial 3D printers, especially when it comes to metal parts where performance and safety are paramount.“

Tim Simpson

Director of Additive Manufacturing and Design Graduate Program at Penn State University

“Shapetag is the first scalable neural network tag scanner that uses machine learning algorithms and artificial intelligence models to accurately decode aesthetically pleasing geometric contours. Furthermore, Shapetags will be almost impossible to decode without using neural networks. We are building technology that becomes invisible so the art of the tag can shine!“

Satya Mallick

Interim CEO, OpenCV

Testimonials

“Shape Matrix technology is a game changer for authentication and anti-counterfeiting. I have tested no other tag system that can embed its tags into 3D-printed parts and then ensure the veracity of the part through off-the-shelf scanning technologies. QR codes and barcodes are too difficult to include in 3D printed parts today given the resolution and scale of today’s commercial 3D printers, especially when it comes to metal parts where performance and safety are paramount.“

Tim Simpson

Director of Additive Manufacturing and Design Graduate Program at Penn State University

“Shapetag is the first scalable neural network tag scanner that uses machine learning algorithms and artificial intelligence models to accurately decode aesthetically pleasing geometric contours. Furthermore, Shapetags will be almost impossible to decode without using neural networks. We are building technology that becomes invisible so the art of the tag can shine!“

Satya Mallick

Interim CEO, OpenCV