Every year millions of cancer cases go undetected until it is too late. Current diagnostic methods are invasive, slow, and dependent on large clinical infrastructure that is out of reach for much of the world. We are changing that.
Cellosyncra is an AI powered diagnostic platform that detects cancer at the cellular level in real time, using nothing more than a compact device and a mobile application. Our approach is fundamentally different from anything on the market today. Rather than relying on existing datasets that are noisy, inconsistent, and unverified, we built our own gold standard dataset from scratch. We record live cells directly under a microscope while mechanically and chemically stimulating them to reveal distinctive behaviors that distinguish healthy cells from abnormal ones. Every cell is verified by human experts in real time, synchronized with high-resolution camera recording. This controlled environment eliminates biological noise and produces the kind of clean, reliable data that makes AI models actually work in clinical settings.
We have developed a deep learning model that captures both the shape of a cell and how it behaves over time, combining spatial and temporal intelligence in a single pipeline. The result is a compact, portable diagnostic device paired with a mobile application that provides clinicians and technicians with clear visualizations and early indicators of abnormal cellular activity.
The market opportunity is significant. Cellosyncra offers a simpler, faster, and far less invasive alternative to traditional cancer detection, with applications in clinical diagnostics, point of care testing, and global health settings where access to conventional diagnostic infrastructure is limited.
We are not just building a smarter algorithm. We are building a new kind of diagnostic pipeline from data to device to patient, and we believe it has the potential to save lives at scale.