An AI platform built around the judgment of surgeons: how they perceive the operative field, and how they reason through a case. Developed first in arthroscopy and sports medicine.
Every field we enter runs on expertise that lives in people. The surgeon who reads a joint in a glance, who senses which way a case is turning before the data confirms it. That judgment is the hardest thing to build and the easiest to lose.
We do not bolt intelligence onto an existing tool. We engineer expertise into the architecture itself: into how a system perceives, and how it reasons. Expertise is not a feature we reference. It is the material the system is made of.
Imaging becomes a working model, and the model carries into the room.
Patient-specific 3D anatomy, reconstructed from MRI.
A working digital twin of the joint, built from the reconstruction.
AI perception of the operative field, in real time.
The plan and the twin, registered to the patient in the room.
Trained on video from real surgeries: the operative field as it actually appears, not a simulation of it. The kind of grounding a model cannot be given after the fact.
A portfolio of provisional patent applications across the platform's imaging, perception, and spatial-intelligence systems.
We started in surgery, the most demanding test of the idea. The same architecture that works in the arthroscopic suite extends across the arc of a surgical case, and into other surgical domains.
Where there is deep expertise and a high cost of error, there is a system worth building.
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