Blogs
Playbook: Policy-Based Daycare Safety Monitorin...
Most childcare programs don’t have a camera problem. They have a decision problem. This playbook shows how policy-driven monitoring turns motion noise into verified incidents—during working hours—without rip-and-replace.
Policy-Based Alarm Verification: The SOC Scalin...
Most monitoring centers aren’t losing because they lack cameras or AI. They’re losing because their queue is full of noise. This playbook explains how Policy-Based Alarm Verification standardizes decisions, reduces handle...
The problem with “fixed” AI and video analytics
Most “AI video analytics” look great in demos because demos are controlled. Real sites are messy: bad angles, glare, rain, snow, busy backgrounds, and cameras installed for coverage—not analytics. This...
Alarm Verification at Scale: A Practical Guide ...
Most monitoring platform “replacements” fail for one reason: they modernize the UI, not the work. This playbook shows RVM/SOC teams how to kill noise, shrink queues, and scale verified response...
AI + Intelligent Automation in Physical Security
Security didn’t lose because cameras are bad. Security lost because humans can’t process infinite video. This post explains the science behind alert overload, the difference between AI and Intelligent Automation (IA),...
From Motion to Judgment: Why “Intelligent Autom...
If your automation strategy is “detect motion → generate alarm,” you didn’t automate security—you automated noise. Real Intelligent Automation (IA) is decisioning: interpreting context, applying policy, handling exceptions, and escalating only...
Property Manager’s Security Buyer’s Guide (Nort...
Most property portfolios already have cameras, access control, and policies. The real failure is operational: too many non-events, slow verification, and no defensible evidence when something actually happens. This guide...
Property Managers’ Playbook: How to Choose Vide...
Most “video security” plans fail for one reason: you’re buying cameras, but you’re not buying outcomes (verified incidents, faster response, fewer false alarms, lower liability). This guide gives you a vendor...
Continuous Video Monitoring: The Real Definitio...
Most people think continuous monitoring means a guard staring at a wall of screens. That model doesn’t scale—financially or cognitively. Modern continuous monitoring is AI-first triage + exception-based human action, with...
After-Hours Shopping Mall Security: The 15-Day ...
Most malls don’t have a “security problem.” They have a signal problem. After hours, your cameras and sensors generate a flood of low-quality alerts—cleaners, reflections, doors, headlights, weather—so humans either ignore...
Shopping Mall Security in North America: The Re...
Malls don’t lose the security game because they lack cameras. They lose because their security operation is drowning in noise. When 90%+ of alarms are non-events, operators burn out, guards chase...
The Cheapest “Guard” a Car Dealership Can Hire ...
If your dealership’s “after-hours security” is basically: cameras record → alarms spam → nobody trusts them → police stop responding… you’re not protected—you’re just collecting footage of your losses. Ranger...
Built for Low-Margin Monitoring: Stop Paying fo...
If you run a monitoring center, your biggest “cost” isn’t labor or dispatch fees—it’s operator minutes wasted on non-events. This post breaks down the RVM margin trap, why “AI pricing” gets...
AI Alarm Filtering Is the New “First Responder”...
Your operators aren’t failing. Your alarm stream is. If your queue is full of “nothing,” you’re not running Remote Video Monitoring—you’re running remote guessing. Ranger filters nuisance alarms before they hit...
Top AI Alarm-Filtering Platforms for Remote Vid...
If you’re shopping for “AI security cameras,” you’re probably buying the wrong solution. Monitoring centers don’t need more video — they need less noise. This post ranks the leading platforms by...
After-Hours Monitoring Is a Margin Trap (Unless...
Most “after-hours monitoring” programs don’t fail because the team is weak. They fail because the queue is loud. When 90–99% of alarm calls to police are false, your monitoring operation...
