Intelligent Physical Security That Sees What Human Guards Miss
AI-enhanced video security combines computer vision with behavioral analysis to detect threats, unauthorized access, and suspicious behavior in real time — dramatically improving detection accuracy while reducing the monitoring burden on physical security teams.
What RLM Delivers on AI Video Security
Traditional CCTV monitoring requires constant human attention that can't be maintained at scale. AI video security monitors continuously, detects anomalies automatically, and alerts security teams only when human judgment is needed — improving detection quality while reducing the monitoring cost.
How We Approach AI Video Security
A structured path through the AI Video Security decision — current-state discovery, shortlist and benchmark, commercial negotiation, then support until it is actually working.
Physical Security Assessment
We assess your current physical security posture — camera coverage, monitoring operations, incident response times, and detection gap analysis — to identify where AI video security would have the greatest impact.
Platform Evaluation
We evaluate AI video security platforms — Avigilon, Genetec with AI add-ons, Verkada, Axis AI, and others — against your physical security requirements, existing infrastructure, and integration with access control systems.
Alert Configuration & Response Workflow
We design the detection scenarios, alert thresholds, and response workflows that balance detection sensitivity with manageable alert volume — ensuring security personnel can act on alerts without alert fatigue.
Integration with Access Control & PSIM
AI video security delivers full value when integrated with access control and PSIM platforms — correlating video events with access events, automating lockdowns, and providing unified incident views.
AI Video Security Selection Criteria
Before committing to any AI Video Security platform, these are the points worth forcing a straight answer on.
Detection Accuracy in Low-Light & Adverse Conditions
Security cameras often need to operate in challenging lighting, weather, and scene conditions. Evaluate detection accuracy specifically in the environmental conditions present at your facilities.
Person Re-identification Across Cameras
Tracking individuals across multiple camera views is critical for post-incident investigation and active threat response. Evaluate re-identification capability and accuracy.
Alert Volume Management
Security AI that generates hundreds of alerts per day creates the same fatigue as no AI. Evaluate the noise reduction capabilities that keep alert volume at a level security teams can meaningfully respond to.
Integration with Access Control
Correlating video events with access control events — unlocking at an alarmed door, tailgating after authorized access — dramatically improves detection accuracy. Evaluate integration depth with your access control system.
Privacy & Legal Compliance
AI video security involving facial recognition or behavioral analysis has specific legal requirements that vary by jurisdiction. Evaluate compliance posture and data handling practices before deployment.
Forensic Search Capability
Post-incident investigation requires the ability to search video archives by appearance, behavior, or event type. Evaluate forensic search capability and the time required to locate relevant footage.
"RLM brought structure to a process we didn't know how to start. They asked the right questions, surfaced the right vendors, and kept us from making decisions we would have regretted."
The benchmark comes first. Without a baseline, “savings” is just a number a vendor gave you.
Where This Matters Most
Sector-specific considerations we see repeatedly in ai and automation engagements.
A Sample of the AI & Automation Providers We Evaluate






RLM is vendor neutral. These are among 600+ providers in our evaluation set — inclusion here is not an endorsement, and we are paid by the provider you choose, not by any provider in particular. How that works →
Thinking About AI Video Security?
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