The problem

In the United States, more than 37,000 lives per year are lost in automobile accidents. Worldwide, an unbelievable 1.25 million people die from car crashes annually.

Fully self-driving automotive technology promises to reduce these accident rates, but it is still years away – many experts say it will be ten years before cars can drive as well as humans. It will take an additional ten years to replace the old automotive fleet with new cars equipped with self-driving technology.


Do we really have to wait twenty years to reduce the cost in blood and treasure from accidents on the roads?

No: there’s something we can do today. We don’t need full self-driving technology, and we don’t need new cars. We can add computer vision and machine learning technology to existing cars to help people drive more safely, today, in the car they already own.


ZipCam makes intelligent, cloud-connected dashcams to make human drivers safer. Front-facing and driver-facing cameras record high-resolution video, and upload driving incidents to the cloud.

Our proprietary driver scoring algorithms use deep neural networks to understand the dynamics of accidents, near-misses, and other driving behavior. Our web-based video dashboard empowers professional driving instructors to bring customized coaching to individual drivers.

ZipCam’s computer vision algorithms constantly scan the roadway to detect pedestrians, bicycles, and other vehicles, and to predict what they will do next. We can identify stop signs, red lights, and read speed limit signs. Inside the cabin, we can detect when the driver is distracted – for example when they are talking to a passenger, or using a cell phone.

We don’t have to wait for fully autonomous cars to make our roads safer.


Michael Palmer

Yale (B.S., Physics), Caltech (Ph.D., Computer Science), Thinking Machines, Intel, SGI, Inktomi (CTO, Search Division), Stanford, Band of Angels, Peloton Technology (Director of Research)

Chuck Abronson

Amplica, EEsof, CAP Wireless, Aggregage, Accordance Ventures

Gary Bradski

Member of Stanley team (winner of DARPA Grand Challenge 2005) from Stanford. Author of  OpenCV, the dominant open-source Computer Vision library. Willow Garage, Industrial Perception (acq. by Google), Magic Leap, Arraiy

Paul Foster

Georgia Tech., U. Michigan,,

John Rockwell

3M, Luxar, Advent International, Element Partners, Accelergy Corporation

Ralph Thomas

SGI, Yahoo!, Palm, Meta, Tesla


ZipCam is located in Palo Alto, CA. We’re hiring!