Add AI to the cameras you already own.

The question most operators actually have.

The sites you monitor already have cameras. Some are five years old, some are new, and they are rarely from one manufacturer. Some sites run a professional VMS, some an NVR web page, some a cloud camera app. You want AI to help your guards, but you cannot re-equip every client site, and you do not control most of those systems.

So the real question is not “which AI is best?” It is “which route gets AI onto these cameras, at these sites, with the access we actually have?” Here are the five options, category by category.

Option 1: Replace cameras with AI cameras.

Many current cameras run object detection on the camera itself and send smart events such as “person in zone.”

• Pros: Analytics run at the edge with full-resolution video. Good for new builds and for a single critical view like a gate.
• Cons: Hardware cost, installation labor and truck rolls for every camera. Mixed fleets end up with mixed analytics. Events still need to reach an operator in a useful form. The on-camera models are usually limited to simple classes and rules.
• Best for: Sites already due for a camera refresh.

Option 2: VMS plugins and analytics modules.

Many VMS platforms offer analytics add-ons, either built in or through a marketplace of third-party plugins.

• Pros: Alerts appear inside the software operators already use. Tight integration with recording, bookmarks and alarm handling.
• Cons: Tied to one VMS. Needs administrator access, licenses and often a server upgrade on the client’s system. A guard company monitoring ten clients on six platforms faces six integration projects.
• Best for: A single enterprise site you control end to end.

Option 3: NVR-level analytics.

Some recorders run detection across connected cameras, or a separate analytics box sits beside the NVR and pulls streams.

• Pros: Adds detection to older cameras without replacing them. One device per site.
• Cons: Hardware per site. Needs camera stream credentials and network access. Channel limits and processing power cap how many cameras get analyzed. Updating models means touching every box.
• Best for: Small single-site owners with one recorder.

Option 4: Cloud bridges.

A small appliance at the site forwards camera streams or clips to a cloud platform that runs the analytics.

• Pros: Powerful models, central management, remote access for multiple sites.
• Cons: Hardware and install per site, stream credentials, upload bandwidth and ongoing per-camera subscription fees. Client IT teams may object to sending video off site. See edge vs cloud video analytics.
• Best for: Multi-site owners willing to standardize on one platform.

Option 5: Screen-based AI.

Screen-based AI works from what the operator already sees: the rendered monitoring screen, whether that is a VMS client, a video wall, an NVR web page or a cloud camera dashboard. It separates the camera panes on screen and analyzes each one.

• Pros: No camera credentials, no vendor API, no changes to the client’s system. Works across mixed camera software at once. Setup happens at the monitoring station, not at every site. Analysis covers what the guard is actually responsible for watching.
• Cons: Analyzes the displayed image, so detail depends on tile size and layout. Cameras not on screen are not analyzed; a good system says so explicitly rather than implying coverage. Deep recording-side features like bookmarks stay in the VMS.
• Best for: Guard companies, monitoring centers and GSOCs watching many sites on many platforms.

How to choose.

Ask three questions. Who controls the cameras? If it is your clients, anything needing credentials becomes a negotiation per site. How many platforms do you see? One favors a plugin; many favor screen-based. Where does the guard work? AI that lands alerts in a separate tool the guard never opens does not help. The screen-based vs VMS-integrated analytics comparison goes deeper.

The routes are not exclusive. A site with AI cameras on the gate can still benefit from screen-based review across every other view on the desk.

Weighing new hardware against software? Our side-by-side of AI security cameras vs. AI software covers cost, rollout and lock-in.

Where Semaphor fits.

Semaphor is the screen-based route, built for operators. It works with your existing camera software by capturing the monitoring screen, separating each camera pane and giving each view its own identity, so it can follow cameras as layouts cycle, resize or rearrange. A camera that cycles off screen is marked unobserved, never assumed quiet.

Local person and vehicle detection flags activity, a preliminary alert lands in the guard inbox immediately, and a vision-language model adds a scene report beside the original frames. Keep the cameras, NVRs, VMS and cloud apps your clients already use. A new client site becomes a new window on the station, not a new integration project.

Book a live demo on your own camera screens, or start a pilot on one monitoring station.

Existing camera questions.