A security team starts noticing a pattern at one of their sites.
One particular camera keeps generating similar alerts. The alerts are reviewed, and guards often report that there is nothing to act on. But the system continues to treat each new alert the same way. It knows what the camera is detecting, but it doesn't know the context behind it. It doesn't know what happened with previous alerts, what the guards found, or whether nearby cameras are seeing anything that could help explain what's happening.
That raised an important question for us:
What if the system could learn from what happened before?
That's the idea behind our Site Intelligence Layer.
When a new alert comes in, it looks beyond the current detection. It considers the site's own rules, recent alert history from that specific camera, activity from nearby cameras, and previous feedback from guards.
That history can change how an alert is understood.
If similar alerts from a camera have repeatedly been reviewed and found harmless, that pattern becomes part of the context. If nearby cameras are showing related activity, that matters too. The system then provides a priority along with a clear explanation of why the alert received that priority. That priority becomes another input into the final escalation decision, alongside the AI vision analysis and the real-time alert level.
The goal isn't simply to generate alerts.
It's to make each alert more meaningful by understanding what is happening now, what happened before, and what is happening around it.
Because security teams don't just need more alerts. They need the right context to know which ones deserve their attention.
