# What is video analytics software? > Video analytics software is a category of intelligent surveillance technology that uses algorithms — increasingly powered by AI and deep learning — to automatically analyse video feeds from security c Canonical URL: https://safetyscope.eu/glossary/video-analytics-software _Published: 2025-10-29 · Updated: 2026-04-02_ Video analytics software is a category of intelligent surveillance technology that uses algorithms — increasingly powered by AI and deep learning — to automatically analyse video feeds from security cameras, extracting actionable information such as object detections, behaviour patterns, and security events. It sits on top of existing camera infrastructure and video management systems, adding an intelligence layer that turns raw footage into operational insight. ## What video analytics software does Video analytics software processes live or recorded video feeds and applies detection, classification, and behavioural analysis to identify security-relevant events. It operates as a layer above the [video management system](/glossary/video-management-software-vms) (VMS), which handles camera connectivity, recording, and storage. When the analytics engine detects a defined event — a person entering a restricted zone, a vehicle stopping in a no-parking area, a crowd forming unexpectedly — it generates an alert. Alerts are routed through a configurable workflow: dashboard notification, mobile push, email, SMS, or integration with a [physical security information management](/glossary/what-is-psim) (PSIM) platform. The core value proposition is simple: video analytics watches every camera, every second, so human operators don't have to. It surfaces only the events that matter, allowing security teams to focus on response rather than observation. ## Rule-based vs AI-based video analytics The video analytics market is split between two fundamentally different approaches. [Rule-based analytics](/compare/rule-based-vs-ai-video-analytics) rely on manually defined triggers — [virtual tripwires](/glossary/virtual-tripwire-security), pixel-change thresholds, fixed zone boundaries. They are deterministic and predictable but rigid. They struggle with environmental variation (weather, lighting) and generate high [false-positive](/glossary/false-positive-security-cameras) rates in dynamic outdoor scenes. AI-based analytics use deep-learning models trained on large datasets to classify objects and behaviours. They adapt to environmental conditions, distinguish between object types (person vs animal vs vehicle), and handle edge cases that rule-based systems cannot anticipate. The trade-off is computational cost: AI models require more processing power, though [edge computing](/glossary/edge-ai-physical-security) and model optimisation have made this increasingly affordable. For most modern security deployments, AI-based analytics deliver materially better outcomes — fewer false alarms, more accurate detection, and the ability to handle complex scenarios without constant rule tuning. ## Core features to look for ### Accuracy and false-positive rate The single most important metric for video analytics is the ratio of genuine alerts to false alarms. A system with high accuracy but an unacceptable false-positive rate will erode operator trust. Look for vendors who publish detection rates and false-positive benchmarks on security-specific datasets, not generic [computer vision](/glossary/computer-vision-security) leaderboards. ### Integration compatibility Video analytics must work with your existing camera estate and VMS. [ONVIF](/glossary/what-is-onvif) and [RTSP](/integrations/rtsp-ip-camera-stream-integration) support are the minimum requirements. Native integrations with popular VMS platforms — Milestone, Genetec, Avigilon — reduce deployment complexity and support costs. ### Deployment flexibility Some platforms run analytics at the edge (on the camera or an on-site appliance), others in a private cloud or data centre, and some offer hybrid architectures. The right choice depends on bandwidth, latency, and data-sovereignty requirements. ### Alert management Raw detections are only useful if the alert workflow is well-designed. Look for configurable escalation paths, suppression rules (to avoid alert flooding), and integration with incident management or PSIM systems. ## Video analytics software and SafetyScope SafetyScope's Omni platform is an AI-native video analytics solution designed for physical security. It integrates with standard IP cameras via ONVIF and RTSP, layers detection and classification models trained on security-relevant data, and provides a unified alert management interface — reducing the gap between detection and response. ## FAQ ### What is video analytics software? Video analytics software is technology that uses algorithms — often powered by AI — to automatically analyse security camera feeds, identifying objects, behaviours, and events and generating alerts without requiring constant human monitoring. ### What is the difference between rule-based and AI-based video analytics? Rule-based analytics use manually defined triggers like tripwires and pixel-change thresholds. AI-based analytics use deep-learning models to classify objects and behaviours, adapting to conditions and producing far fewer false alarms. ### Does video analytics software work with existing cameras? Yes. Most video analytics platforms integrate with standard IP cameras that support ONVIF or RTSP protocols, meaning you typically do not need to replace your existing camera infrastructure. ### What is VCA (video content analysis)? VCA — video content analysis — is an older industry term for what is now commonly called video analytics. It refers to the automated extraction of information from video feeds, including motion detection, object tracking, and event recognition. ### How does video analytics software integrate with a VMS? Video analytics typically runs alongside or on top of a VMS. It receives camera feeds via the VMS or directly from cameras, processes them, and pushes alerts back into the VMS interface or to external systems via APIs.