A documented comparison for security teams looking at an automation layer over the systems they already run. Cobalt AI names the video platforms it connects to, which almost nobody in this category does. The question is whether you need a layer on top or intelligence in the platform itself.
Cobalt AI sells Cobalt Monitoring Intelligence, an automation layer that connects to the cameras, access control systems and edge devices a site already runs, then reasons across them to surface root cause and drive response workflows. For video it names Eagle Eye Networks, Milestone XProtect, Genetec and any RTSP or RTSPS stream. Teams shop for an alternative when they would rather have one platform than a layer over several, when the video AI itself is the gap, or when something has to happen on site after the alert. The five below answer those differently.
Both routes end with an operator getting fewer and better alerts. One reasons across the systems already installed, the other replaces what the cameras are asked in the first place.
Every cell is something the vendor publishes, or an explicit not publicly specified.
Swipe the table sideways to see every column.
Cobalt AI's row was read off cobaltai.com on August 12, 2026, including the named video integrations and the edge, cloud or hybrid deployment statement. The other five rows come from each vendor's public documentation reviewed in July and August 2026 on the same five columns. Gaps are marked as not publicly specified rather than guessed.
Start by discarding the wrong reason, and give Cobalt real credit while you are here. It is not vague about interoperability, which is the single most common failure in this category. It names the video platforms it works with, Eagle Eye Networks, Milestone XProtect and Genetec, plus any RTSP or RTSPS stream, and it names the workflow systems too: Okta for identity, ServiceNow and Salesforce for ticketing, Slack, phone, SMS and email for communication. That is a shortlist you can check against your own stack before a call.
The first real reason is that a layer assumes a stack worth layering over. Cobalt's value comes from reasoning across cameras, access control and edge devices you already run, so if your video platform is the weak part, the layer inherits that weakness. A tailgating handler that verifies badges against video is only as good as the video AI underneath it, and Cobalt is not selling you that AI.
The second is what happens on site. Cobalt documents detect, reason, act and resolve, and the act is a workflow: a service ticket, an escalation, a cleared alarm, an operator freed up. At Salesforce it reports returning over 6,000 hours of operator time per month, which is a real operations result. What the public pages do not document is a speaker, a talk down or a strobe, so nothing happens in the yard while the workflow runs.
Cobalt is buying your operators time back. If the gap is what the cameras actually notice, a layer over the same cameras will not close it.
What each one is, where it is strong, and what to check before you commit.
Spot AI is a software-led video AI platform that turns the IP cameras a business already owns into AI coworkers. An on-site Intelligent Video Recorder keeps full-resolution video in the building and sends only event metadata to the cloud, so search and multi-site management stay cloud-based while footage does not leave the facility.
Verkada is a cloud-managed platform that sells its own cameras, access control, sensors, alarms and intercoms under one console, and publishes per-device MSRPs, which is unusual in this market. Third-party cameras come in through Command Connector, which Verkada states is an ONVIF Profile S conformant client and can also ingest RTSP feeds.
Eagle Eye Networks is a cloud video management system that connects to virtually any ONVIF-conformant camera and digitises analog feeds through analog-ready Bridges and CMVRs, then layers cloud analytics on top of the estate. Its documentation names ONVIF Profile S and dual codec streaming as the integration path.
Genetec Security Center unifies access control, video, automatic license plate recognition and communications in one platform, built from named modules: Omnicast for video, Synergis for access control, AutoVu for license plate recognition, Sipelia for communications and Mission Control for decision management. Genetec states its solutions are non-proprietary and built on open architecture.
Rhombus sells cloud-managed cameras, sensors, access control and alarm monitoring as one system, described by the company as a cloud-edge system that operates offline. Third-party cameras come in through the Relay Connector N100, and the company publishes SOC 2, NDAA, GDPR and TAA compliance badges.
Six questions that separate these platforms faster than any feature list.
Count your systems. If cameras, access control, alarms and sensors are four consoles and four alert streams, an automation layer is aimed exactly at that. If the complaint is that the cameras miss things, or only answer security questions, the gap is in the video AI and layering over it changes nothing.
Cobalt names Eagle Eye Networks, Milestone XProtect, Genetec and any RTSP or RTSPS stream. That is more specific than most vendors here manage. Check your own VMS and access control against every vendor's named list, in writing, and treat any camera outside it as a project rather than a line item.
Ask what occurs the moment a person is detected in a yard at 02:00. Cobalt documents reasoning, tickets and escalation. Eagle Eye documents sirens and talk-down. Verkada gates automated audio to the BZ11 or an Intercom. Spot AI runs talk down, strobes and horns through standard speakers already mounted.
Cobalt names gun detection, tailgating with badge verification and door forced open. Eagle Eye names four analytics. Spot AI ships 15+ pre-trained agents plus Iris for custom detections. Rhombus and Genetec publish no detection list. Ask each vendor for the shipped list and mark it against your own requirements before any demo.
A layer is an additional subscription on top of the platforms it reasons across. Add them up over three years, including the VMS, the access control, the layer and any monitoring service, then compare that against one platform that covers video AI directly. The count of renewals is a cost nobody puts on a quote.
Rhombus states SOC 2, NDAA, GDPR and TAA. Spot AI states SOC 2 and NDAA. Cobalt AI and Eagle Eye name none on the pages read. For a platform that reasons across badge logs and video together, that question deserves an answer in writing on the first call.
Spot AI fits when the cameras are the thing to fix. It runs on any ONVIF or RTSP camera plus legacy analog through the Intelligent Video Recorder, keeps full-resolution video in the building, ships 15+ pre-trained agents across security, safety and operations, and acts through standard speakers rather than routing every event to a person.
Cobalt AI stays the right call for an enterprise that already runs good systems, has operators buried in alarms, and wants root cause and response automated across all of them. Its named integration list and the Salesforce result are the strongest evidence on this page that the layer model works when the stack underneath is sound.
A camera-agnostic platform lets you test the AI on your own cameras before any hardware decision, which is the cheapest way to de-risk the choice.
Watch the AI coworkers work on your live feeds, not a demo reel.
Customer-reported outcomes from named Spot AI customers.
Cambridge City cut the time it takes to find footage from two hours to thirty seconds.
Don Franklin Family of Dealerships had video of an incident on responding officers' phones within four minutes of the alarm, and recorded five recoveries within the hour.
Bridge33 Capital standardized video across 25 plus commercial properties on whatever cameras each acquisition already had, and cut footage search from hours to minutes.
"The Spot AI notification went out around one in the morning, and police were able to arrive on-site while the incident was still in progress."
The five covered here are Spot AI, Verkada, Eagle Eye Networks, Genetec and Rhombus. Spot AI fits teams whose gap is the video AI itself. Verkada fits a greenfield single-vendor build. Eagle Eye Networks fits mixed and partly analog estates. Genetec fits large unified estates. Rhombus fits mid-market teams wanting one vendor rather than a layer.
Yes, and it is specific. Cobalt states the platform layers over existing infrastructure with no overhaul required, and for video it names Eagle Eye Networks, Milestone XProtect, Genetec and any RTSP or RTSPS camera stream. It also names Okta, ServiceNow, Salesforce and Slack on the workflow side. Check your own VMS against that list before shortlisting.
Its published examples are gun detection identifying firearms on camera in real time, a tailgating handler that verifies badges against video, and door-forced-open events reasoned against video, badge logs and device health. No speaker, talk down or strobe behaviour appears on its public pages.
No, by design. It is an automation and monitoring intelligence layer that connects to the cameras and access control you already run, supporting edge, cloud or hybrid deployment. That is the distinction worth holding onto when comparing it with the platforms on this page, which sell the video layer itself.
No. No list price, per-camera figure, plan tier or contract term appears on its site. Of the platforms compared here, only Verkada publishes per-device MSRPs. Because a layer sits on top of subscriptions you are already paying, ask for the three-year total across every contract on the same camera fleet.