Kortx continuously senses objects, still or in motion, and captures them in precise 3D, giving robots real-time perception and giving AI the physics that video can't capture.
Machine perception today is built on frame cameras: every pixel, every frame, on a fixed clock, whether or not anything changed. That is not how our eyes work.
A single frame captures a flat, frozen instant. Depth takes more frames: a second view to triangulate, or a sequence of projected patterns. Change takes more frames too, since motion only appears by comparing one snapshot to the next. Everything a frame system knows, it infers by stacking snapshots, and every snapshot costs time.
Between snapshots, it is blind. The moments that matter, the contact, the slip, the sudden stop, can happen in the gaps. Faster chips and better glass don't change the rule.
Factories use rigid precision to enable automation. Stop stations, precision fixtures, precise tooling: the world held exactly where the machine expects it.
Vision's job is to absorb the variability that remains. And frame vision does, but only a little. Even a precisely fixtured assembly often varies enough, part to part, that a robot cannot place the next piece blind, so vision locates the feature and the robot corrects. That is frame vision at its best: absorbing millimeters of variation, in a stopped, fixtured, carefully lit world.
Everything that varies more than that stays manual. Caging those processes tightly enough for frame vision costs more than the labor it would replace. That is the Infrastructure Tax.
The boundary of automation is set by how much variability the robot and its perception can absorb, and frames absorb only a little.
Kortx does not take faster pictures. It does not take pictures at all.
It senses the world the way eyes do: reacting to change, continuously, pixel by pixel, in millionths of a second. And it creates its own signal: a scanning laser marks the scene point by point, and the sensors capture each mark the instant it appears. Moving part or still part, Kortx measures precise 3D.
The laser is what separates measuring from guessing. Other technologies project a coarse pattern of dots only to give their algorithm something to match, then infer depth, and only where a part's shape gives it away. Kortx measures distance precisely.
Precision lives in the software, not in a precisely built sensor. Kortx does not need expensive lenses or a perfect optical build. The software provides the precision, so the hardware can focus on robustness: surviving the real world.
This is not a better camera. It is a different kind of vision, a new category of industrial perception.
Because the data is a continuous stream, not a fixed frame, Kortx reads it two ways at once. Reading a few milliseconds of the stream tracks a moving part and guides a robot as it moves. Reading about a second of the same stream builds a dense, precise 3D point cloud, detailed enough to inspect that same part for defects and measurement. The old choice between fast and precise disappears: one sensor does both, in a single pass.
One data stream, read two ways: a fast, sparse read to track a moving part, and a denser read that builds up over time to model and inspect it. Same stream, same part.
And over time, the stream teaches. Today's AI learns the physical world mostly from video, and video is flat: it shows what a thing does, but not in 3D. The contact, the give of a surface, the speed of a fall: the physics is missing. Kortx captures exactly that layer: what moved, when, in precise 3D.
The same data that lets a robot act in the moment teaches a model what physics looks like.
This does not compete for the existing machine-vision budget. It automates tasks that until now could only be done by hand, and it gives physical AI a kind of data it has never had.
Kortx is in active programs today with global leaders across automotive, semiconductor manufacturing, and medical robotics. The hardest factory floors are our proving ground. The perception that survives them, precise 3D in motion, in bad light, on impossible surfaces, is the sensory layer embodied AI has been missing. We earn the future by mastering the present.
That is not a larger share of a market. It is a new one.