Intelligence for the physical world.
SenseMind is an intelligent vision company. We give machines the ability to see, measure and reason about their surroundings — and we make that intelligence small enough to live inside the device, wherever the work happens. SenseMind 是一家智能视觉系统公司。我们让机器看见、测量并理解周遭环境,并把这份智能压进设备本身,跟着场景一起走。
For a decade, AI learned to read, write and reason — about words and pixels on a screen.
The next decade is about teaching it to see — and to act on what it sees.
一座工厂、一个十字路口、一片农田、一条输电线、一辆行驶中卡车的车厢——凡是摄像头注视真实世界的地方,都有等待被建立的智能。我们要把它建起来:在设备上,实时地,在现实本就杂乱的光线与运动里。
Why intelligence is moving to the edge.
Three forces are pulling perception out of the data center and onto the device itself.
Sensors everywhere传感器无处不在
The world is filling with cameras. The streams they produce are too large, too fast and too sensitive to send to the cloud and wait for an answer.
Silicon got cheap算力变得廉价
Vision accelerators now cost a few dollars and draw a few watts. Real inference no longer needs a server — it fits in the palm of the device.
Models can be shrunk模型可以被压缩
What once demanded a GPU can be distilled and quantized to run on that small chip, keeping the accuracy that actually matters.
The bottleneck is no longer cameras or compute. It is perception software built to survive contact with the real world — and that is exactly what we make.
One perception stack, end to end.
From the raw sensor to a decision the device can act on — without a network in the loop.
On-device deployment边缘端部署
Models distilled and quantized for low-power vision chips, tuned so the loss that matters stays inside tolerance on real hardware.
Perception algorithms感知算法
Detection, segmentation and metric 3D — recovering not just what is in a scene, but where it is and how much of it there is.
Spatial & temporal reasoning时空推理
Tracking, occupancy and accumulation that fuse a stream of frames into one coherent, stable picture of a scene over time.
Synthetic-to-real data合成到真实
A simulation-driven data engine that builds reliable models where real labels are scarce, costly or dangerous to gather.
One core. Many physical worlds.
The same perception engine, hardened for the environments where value physically moves and changes.
Mobility & Vehicles车载与出行
Perception that rides with the asset — on trucks, machines and moving platforms, where conditions never sit still.
Logistics & Supply Chain物流与供应链
Reading cargo, space and flow — from the loading bay to the inside of a container.
Industry & Inspection工业与质检
Dimensioning, counting and anomaly detection at the line speed of a real operation.
Infrastructure & Energy基础设施与能源
Inspecting structures, lines and sites from the ground or the air, where sending people is slow or unsafe.
Robotics & Automation机器人与自动化
Spatial understanding for machines that move and act — the sense of place that lets autonomy be safe.
Smart Spaces智慧空间
Reading people, objects and movement inside real environments, with privacy kept on the device.
What takes a model from demo to field.
Three commitments that decide whether perception survives outside the lab.
From simulation to reality从仿真到现实
We generate the data the world won't hand us, then engineer the bridge so models trained in simulation hold their footing in the field.
Compression without compromise压缩而不妥协
Frontier accuracy, distilled to fit a chip that costs a few dollars — measured on the silicon, not just in the notebook.
Perception you can trust可信赖的感知
Calibrated confidence and honest uncertainty. The system reports what it sees, and says so when it cannot be sure.