Build your AI camera
on Qualcomm
and skip
a year of engineering

You keep your own relationship with Qualcomm for silicon supply and BSP access. That relationship comes with your hardware purchase, and we can’t transfer it.

We provide a Yocto layer that runs on top of the Qualcomm BSP, plus a team that has already completed bring-up for this silicon.

When Qualcomm releases a new BSP or kernel, our layer needs to be revalidated. That work is scoped as maintenance. This matters because a BSP update can affect camera pipeline behavior in ways that take time to find and fix.

The software layers can move quickly because they already exist. The parts tied to your physical device take longer.

Sensor bring-up and ISP tuning depend on your hardware. If your camera uses a sensor that has not been tuned on this SoC before, this is engineering work. Certification also runs on external lab timelines, including FCC, CE, and any market-specific approvals.

Mechanical, thermal, and power validation for your enclosure remain with your team.

When we say weeks, we mean weeks from stack integration to a working device that can stream, record, search, and update. We do not mean weeks from concept to a certified product on a shelf.

AI alerts are much better than motion detection, but they aren’t perfect.

Vision-language rules understand context, so a branch moving in the wind or a shadow crossing a doorway is less likely to trigger an alert. Some failure cases remain, including unusual camera angles, poor lighting, heavy occlusion, and environment-specific edge cases.

On the first deployment, we tune rules against your footage. A realistic expectation is a few weeks of adjustment before the alerts align well with the site.