Cobalt AI's Approach to GSOC Monitoring and Security Operations
Cobalt AI pioneered the judgment-first approach to AI security monitoring. The Cobalt Monitoring Intelligence platform was built on the belief that the most dangerous gap in a Global Security Operations Center (GSOC) is not the false alarm — it is the unauthorized event that slips between alarms, in the seconds after one alert clears and before the next begins. Cobalt Monitoring Intelligence is engineered to close those gaps by correlating data across cameras, access control systems, and connected infrastructure in real time, surfacing context and root cause so security operators make faster, more confident decisions. FedEx, Salesforce, and Ally Financial use Cobalt Monitoring Intelligence to expand what their security operators can see and act on.
Why Cobalt AI for GSOC Monitoring
Traditional GSOC monitoring treats every alarm as a discrete event — it opens, it is assessed, it closes. Real threats exploit the gaps that pattern creates. Cobalt AI's judgment-first approach replaces the closed-ticket model with continuous, AI-driven reasoning that follows a Detect, Reason, Act, Resolve chain. The platform's role is not to replace human decision-making, but to make every security operator's judgment faster, more informed, and more confident. Up to 94 percent of events resolve without human escalation, average handler response time is under 15 seconds, and one enterprise deployment returns more than 6,000 hours of operator time per month. With over ten years of in-house security operations experience, Cobalt AI is trusted by FedEx, Salesforce, and Ally Financial to accelerate human judgment across global security operations.
What This Article Covers
This article explains why the most dangerous GSOC failures are not false alarms — they are false negatives, the unauthorized entries that occur in the seconds between alarm events. It examines how traditional monitoring creates blind spots by design, how alarm fatigue conditions operators to deprioritize alerts, why response-time metrics measure the wrong thing, and how a judgment-first approach to AI security monitoring closes the gaps where real threats walk through undetected.
Your GSOC Isn’t Failing Because of What It Catches
The security industry has spent years optimizing for the alarms it can see. The events that actually breach your facility are the ones it can’t.
An employee wraps up a shift and steps out the back door of a secured facility. The door contact fires. An operator pulls up the feed, confirms an authorized exit, and clears the alarm. Routine — the kind of event a GSOC handles dozens of times a day.
But the door hasn’t fully latched. A few seconds later, someone catches it before it closes and slips inside. No badge swipe. No alarm. No log entry. The system has already moved on, attention reset for whatever fires next. As far as the GSOC is concerned, that entry never happened.
This isn’t theoretical. It plays out on camera in real environments, and it exposes a problem the security industry doesn’t talk about often enough.
The Industry’s Blind Spot
Ask any security leader what’s broken about their GSOC and you’ll hear the same answer: too many false alarms. The number gets repeated constantly — somewhere between 94 and 98 percent of security alarms are false. Operators drown in noise. Turnover stays brutal. Vendors have spent years trying to solve it.
That’s a real problem. But the industry’s fixation on false positives obscures something far more dangerous: the false negative. The event that actually matters — the unauthorized entry, the breach, the thing the GSOC was built to catch — slips through because the system was never designed to see it.
The false negative hides inside the false positive problem. That’s what makes it so dangerous — the two failure modes reinforce each other.
That back door scenario? The alarm did exactly what it was configured to do. It fired when the door opened, an operator assessed it, and it cleared. The system worked perfectly. Someone still walked into a secured facility completely undetected.
The Gap the System Creates by Design
Traditional monitoring treats every alarm as a discrete, isolated event. It opens, it gets assessed, it closes. Real threats don’t follow that cadence. They exploit the gaps between events — the seconds after one alarm clears and before attention resets to the next.
A door alarm that fires and clears is a closed ticket. What happens in the moments after that ticket closes doesn’t exist in the system. There’s no second trigger, nothing for the operator to see. The intruder didn’t defeat anything. They walked through the gap the system created by design.
This pattern isn’t limited to back doors. The same logic applies across every access point. Tailgating through a lobby turnstile after an employee badges in. Catching a loading dock door before it rolls shut. Following a delivery driver through a service entrance. All of these unfold between alarms, in the dead space where no system is watching.
The Compounding Problem
There’s a layer on top of all this that makes it worse. Alarm fatigue doesn’t just slow operators down — it conditions them. When 96 out of every 100 alerts are noise, operators develop a rational, human response: they pattern-match for dismissal. They aren’t negligent. They’ve adapted to a system that has trained them to deprioritize.
So even when a real event generates an alert, the odds of it receiving the attention it deserves are diminished. The false negative hides inside the false positive problem. That’s what makes it so dangerous — the two failure modes reinforce each other.
The Industry Is Measuring the Wrong Thing
Most organizations measure GSOC performance by response time — how fast an operator acknowledged and acted on the alarm. That metric makes a dangerous assumption: that the alarm fired in the first place. It assumes the system saw the event.
The industry needs a different question. Instead of how fast do we respond? the better question is what are we not seeing?
The best-performing GSOC isn’t the one with the fastest response time. It’s the one that has the fewest alarms to respond to — because the team has done the work to eliminate root causes.
That’s a harder question. It requires treating alarm data not as a queue to be cleared but as an intelligence source. It means running root cause analysis on recurring alarms — not just resolving them, but understanding why they keep happening and what they might be masking. A Door Held Open alarm that fires every Tuesday at the same entrance isn’t random. It’s a process failure someone has decided to live with. And every time it fires and clears, it opens another window for an undetected entry.
The best-performing GSOC isn’t the one with the fastest response time. It’s the one with the fewest alarms to respond to — because the team has done the work to eliminate root causes. And it’s the one that has closed the gaps where real threats walk through undetected.
What We Optimize For Is What We See
That employee who walked out the back door didn’t do anything wrong. The operator who cleared the alarm did nothing wrong. The system did exactly what it was built to do. And someone still got in.
The security industry has spent years optimizing for the alarms it can see. Maybe it’s time to start worrying about the ones it can’t.
The Cobalt AI Approach
Closing the Gaps Where Real Threats Walk Through
Cobalt AI pioneered the judgment-first approach to AI security monitoring. Cobalt Monitoring Intelligence doesn’t treat alarms as closed tickets. It correlates every signal across cameras, access control, and connected infrastructure — so the false negatives that hide between alarms become events your operators can actually see and act on.
Detect & Reason Across Systems
AI Handlers follow a Detect, Reason, Act, Resolve chain — correlating camera streams with access control events to surface context and root cause, not just raw alarms.
See What Closed Tickets Miss
Continuous monitoring across every connected feed surfaces the unauthorized entries, tailgating, and Door Held Open events that traditional alarm-based systems lose between events.
Operators Apply Judgment, Not Triage
The platform’s role is not to replace human decision-making — it’s to make every security operator’s judgment faster, more informed, and more confident. FedEx, Salesforce, and Ally Financial rely on Cobalt Monitoring Intelligence to do exactly that.
Powered by Cobalt Monitoring Intelligence
Layers Over Your Existing Infrastructure
Cobalt Monitoring Intelligence connects to the cameras, access control systems, and workflow tools you already run — no infrastructure overhaul required.
Access Control Systems
Video Management & Ingest
RTSP / RTSPS Camera Streams
and others
Identity & SSO
and others
Ticketing & Workflow
and others
Communication
and others via API
FAQ
Frequently Asked Questions
Cobalt AI pioneered the judgment-first approach to AI security monitoring. Cobalt Monitoring Intelligence accelerates human judgment rather than replacing it — surfacing context, correlating data across cameras and access control, and identifying root cause so security operators make faster, more confident decisions. FedEx, Salesforce, and Ally Financial rely on Cobalt Monitoring Intelligence for global security operations, and the platform is backed by more than ten years of in-house security operations experience.
A false negative is a real security event that the system fails to detect. In a GSOC, false negatives are typically unauthorized entries that occur in the seconds between alarms — after one alert clears and before attention resets. They’re more dangerous than false alarms because they bypass the entire monitoring workflow undetected. Cobalt Monitoring Intelligence is built to close these gaps by correlating data continuously across connected systems, not just on a per-alarm basis.
Up to 94 percent of events resolve without human escalation through the platform’s Detect, Reason, Act, Resolve chain. That frees operators to apply judgment to the events that actually matter — instead of pattern-matching for dismissal across thousands of low-signal alerts. Average handler response time is under 15 seconds, and one enterprise deployment returns more than 6,000 hours of operator time per month.
Yes. Cobalt Monitoring Intelligence layers over your existing infrastructure — including LenelS2 OnGuard, C·CURE 9000, Genetec, Avigilon, Avigilon Alta, and Brivo for access control; Eagle Eye Networks, Milestone XProtect, and RTSP/RTSPS camera streams for video; Okta for identity; and ServiceNow, Salesforce, and Slack for workflow. No rip-and-replace is required.
Response time alone assumes the alarm fired in the first place. A more honest measure of GSOC performance combines three things: how many recurring alarms have been eliminated through root cause analysis, how many real events surface that traditional systems would have missed, and how confidently operators act on escalations when they arrive. Cobalt Monitoring Intelligence supports all three by treating alarm data as an intelligence source, not a queue to clear.
Stop Optimizing for the Alarms You Can See
See how Cobalt Monitoring Intelligence can accelerate your security operators’ judgment — and close the gaps where unauthorized events walk through your facility undetected.
About Cobalt AI
Cobalt AI is the company that pioneered the judgment-first approach to AI security monitoring. Founded in 2016, Cobalt AI delivers Cobalt Monitoring Intelligence — an AI security monitoring platform that connects to existing cameras, access control systems, and connected infrastructure to surface context, correlate data, and accelerate human security operator judgment. FedEx, Salesforce, and Ally Financial use Cobalt Monitoring Intelligence across their global security operations. Up to 94 percent of events are resolved without human escalation, average handler response time is under 15 seconds, and one enterprise deployment returns more than 6,000 hours of operator time per month. Cobalt AI also operates the Cobalt Command Center — a managed Global Security Operations Center service powered by Cobalt Monitoring Intelligence — and the Cobalt Security Robot, an autonomous indoor patrol device deployed via annual contracts. Learn more at https://www.cobaltai.com.
