Top 10 Best Gun Detection Software of 2026

ZeroEyes is an AI-powered gun detection platform that integrates with existing security cameras to provide real-time firearm detection using advanced computer vision technology. It analyzes video feeds 24/7, identifying guns in under three seconds and sending verified alerts to security teams via mobile apps, dispatch systems, or integrations like Motorola Solutions. Designed for proactive threat prevention, it boasts high accuracy with low false positives, making it ideal for high-risk environments such as schools, hospitals, and public venues.

Omnilert is an AI-powered threat detection platform that uses computer vision to identify guns, knives, and active threats in real-time from existing IP cameras and video feeds. It delivers instant alerts to security personnel via mobile apps, email, or integrations with systems like Alertus for mass notifications. Designed for high-security environments like schools, workplaces, and public venues, it minimizes response times to potential gun violence incidents.

Athena Security's Gun Detection software leverages advanced AI and computer vision to analyze live feeds from existing IP cameras, detecting firearms in real-time with high accuracy. Upon detection, it sends instant alerts via SMS, email, or integrated panic buttons to security teams, enabling rapid response. The solution emphasizes low false positives through proprietary algorithms and supports features like person detection and custom deny lists for known safe objects.

Coram AI is an AI-driven video analytics platform that provides real-time detection of guns, knives, and other threats in live surveillance footage from existing CCTV cameras. It analyzes video streams to identify weapons with high accuracy, sending instant alerts to security teams via mobile apps or integrations. The software emphasizes low false positives through advanced machine learning models trained on diverse real-world scenarios, making it suitable for proactive threat mitigation in high-security environments.

Rhombus is a cloud-based physical security platform offering AI-powered video surveillance with integrated gun detection capabilities through its Smart Search analytics. It uses computer vision to detect firearms in real-time or from recordings, triggering customizable alerts for security teams. The system integrates seamlessly with access control, sensors, and other security tools for a unified threat response, making it suitable for enterprise environments.

BriefCam is an AI-powered video analytics platform designed for rapid review, search, and analysis of surveillance footage from multiple cameras. It employs advanced computer vision to detect and classify objects, including firearms, enabling quick identification of gun-related threats amid vast video data. The software supports both live and archived video, providing tools for behavior analysis and incident investigation in security operations.

Ultralytics YOLO is an open-source computer vision library powering state-of-the-art YOLO models for real-time object detection and segmentation. It supports easy training on custom datasets, making it highly adaptable for gun detection in security cameras, surveillance systems, or mobile apps. With versions like YOLOv8 and YOLOv11, it delivers top-tier accuracy and speed on various hardware.

OpenCV is an open-source computer vision and machine learning library that enables developers to build custom gun detection systems using object detection algorithms like YOLO, SSD, or Haar cascades. It provides essential tools for image preprocessing, feature extraction, real-time video analysis, and integration with deep neural networks. While highly versatile, it requires significant custom development and training for reliable gun detection rather than offering a plug-and-play solution.

Roboflow is a versatile computer vision platform designed for building, managing, and deploying custom object detection models, including those for gun detection in images and videos. It offers tools for dataset curation, annotation, augmentation, preprocessing, and training with algorithms like YOLOv8, enabling users to create accurate gun detectors from scratch or fine-tune existing ones. While highly capable for custom CV projects, it requires users to source or create gun-specific datasets rather than providing ready-made gun detection solutions. Its deployment options support edge devices and cloud services for real-time security applications.

The TensorFlow Object Detection API is an open-source framework from Google that provides tools to build, train, and deploy custom object detection models using TensorFlow. For gun detection, it excels in training models on custom datasets of firearms, supporting architectures like SSD, Faster R-CNN, and EfficientDet for real-time or high-accuracy detection. It includes utilities for data preparation, evaluation, and export to formats like TensorFlow Lite for edge deployment, making it adaptable for security applications.