GITNUXSOFTWARE ADVICE
Public Safety CrimeTop 10 Best Gun Detection Software of 2026
Ranking roundup of gun detection software for security teams, comparing tools like Omnilert Gun Detection, Panic Technology, and IntelliSee.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Omnilert Gun Detection is the strongest pick for security operations teams that need consistent, detection-to-incident workflows across connected cameras, whereas Panic Technology Gun Detection fits when you want reviewable gun detections and dependable escalation from CCTV alerts.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Omnilert Gun Detection
Incident-first workflow that links each firearm event to operator review and escalation outcomes within the same handling record.
Built for fits when security operations teams need consistent detection-to-incident workflows across multiple cameras..
Panic Technology Gun Detection
Editor pickOperational workflow that couples firearm classification with human-in-the-loop review before incident escalation.
Built for fits when security teams need reviewable gun detections and consistent escalation from camera alerts..
IntelliSee
Editor pickInvestigation-first human review that ties detection events to on-demand evidence clips for faster incident decisions.
Built for fits when security teams need firearm detection evidence and analyst confirmation from existing VMS workflows..
Related reading
Comparison Table
Omnilert Gun Detection
enterpriseComputer vision detects visible firearms across connected video surveillance systems.
Incident-first workflow that links each firearm event to operator review and escalation outcomes within the same handling record.
Omnilert Gun Detection centers on real-time firearm detection and alerting tied to case creation for investigation and escalation. The workflow supports human-in-the-loop review so operators can confirm or dismiss events before incident outcomes are finalized. The deployment model is built around continuous monitoring of covered camera views and predictable event timing so downstream response teams see events in the same structure.
A key tradeoff is that accuracy depends heavily on camera placement, lighting, and target visibility across the monitored areas. The system fits environments with stable coverage and repeatable patrol or response procedures where operators can triage alerts quickly and document outcomes consistently.
use_cases
- +Human-in-the-loop review for operator confirmation
- +Alert routing tied to incident escalation workflows
- +Consistent event handling from continuous camera feeds
- +Clear separation of detection events and outcomes
- –Accuracy drops when firearms are partially occluded
- –Camera coverage and lighting drive false alarm rates
- –Limited benefit when response procedures are undefined
Security operations center analysts
Triage firearm alerts from live camera feeds
Lower unnecessary dispatches
Facility security leads
Standardize investigations across sites
Faster incident closure
Show 1 more scenario
Loss prevention supervisors
Respond to potential threats in retail back areas
Quicker threat response
Detection events trigger controlled alarm handling for quick verification.
Best for: Fits when security operations teams need consistent detection-to-incident workflows across multiple cameras.
More related reading
Panic Technology Gun Detection
vertical specialistAI-driven gun recognition software that integrates with existing CCTV infrastructure.
Operational workflow that couples firearm classification with human-in-the-loop review before incident escalation.
Security operations teams get a practical path from camera coverage to alerting, with review steps designed to separate detections from actionable incidents. Firearm classification signals help route events by object type instead of treating all detections the same. Automation is oriented around real-time alerting and downstream escalation logic rather than manual-only triage.
A key tradeoff is that performance depends on camera placement, lighting, and field-of-view because model confidence can drop when the target is small or heavily occluded. Panic Technology Gun Detection fits situations where operators want fewer but more reviewable alerts, like perimeter monitoring with dedicated escalation procedures.
- +Human-in-the-loop review reduces alert noise before escalation
- +Firearm classification supports object-type based event handling
- +Real-time alerting supports fast incident response workflows
- +Designed for operational monitoring with camera feed integration
- –Alert quality depends heavily on camera coverage and lighting
- –Advanced tuning needs operational discipline and repeatable validation
- –Throughput can be constrained by the number of concurrent feeds
Security operations center
Route firearm alerts through review
Fewer false alarms escalated
Campus security
Perimeter monitoring with escalation rules
Faster verified incident handling
Show 2 more scenarios
Retail loss prevention
Backroom and entrance surveillance
More consistent reporting
Classified detections feed a review step to support structured incident documentation.
Enterprise facilities team
Central monitoring station coverage
Centralized operational visibility
Events from multiple cameras are handled in a single monitoring workflow with review.
Best for: Fits when security teams need reviewable gun detections and consistent escalation from camera alerts.
IntelliSee
enterpriseVideo intelligence detects weapons and other threats across security camera feeds.
Investigation-first human review that ties detection events to on-demand evidence clips for faster incident decisions.
IntelliSee is positioned for organizations that need firearm detection confidence and repeatable review outcomes, not just image labeling. The workflow design supports investigation after an alert by keeping the video context available for reviewer confirmation. The configuration approach targets camera coverage planning and verification loops that aim to balance false positive rate and false negative rate over time. IntelliSee also fits teams that already run a video management system and want detections to align with that operational surface.
A tradeoff appears in the need for review governance, because human validation is typically required to handle edge cases and low-light scenes. IntelliSee fits facilities with established camera layouts and repeatable shift coverage where analysts can quickly confirm or dismiss alerts and route incidents for escalation.
- +Human-in-the-loop review workflow reduces alert noise
- +Firearm classification oriented models improve verification speed
- +Designed for security operations center alert-to-evidence investigations
- +Camera coverage planning supports repeatable detection outcomes
- –Review governance is required to control incident quality
- –Performance tuning depends on camera placement and lighting conditions
- –Integration effort rises when environments lack standardized VMS workflows
- –Edge cases can still produce false positive detections
Security operations teams
Confirm firearm events from live camera alerts
Lower noise in incident queue
Facility security leads
Verify coverage across parking and entrances
More consistent alerting by area
Show 1 more scenario
Video management system administrators
Route detections into existing monitoring workflows
Fewer tool handoffs during response
Operations align detection events with VMS workflows so evidence stays in the same operational view.
Best for: Fits when security teams need firearm detection evidence and analyst confirmation from existing VMS workflows.
Vaidio
enterpriseAI video search and analytics include firearm and weapon detection capabilities.
Confidence-aware human review routing that ties each firearm classification event to downstream escalation decisions.
Vaidio uses computer vision for firearm detection by generating structured results from camera footage and routing those results into review and alert workflows. The distinct part is its workflow orientation around detection confidence and human-in-the-loop handling to control alarm verification outcomes.
Vaidio supports operational use in security operations center setups by turning detections into trackable events for escalation. Integration depth is geared toward getting video and detection outputs connected to existing monitoring processes through an automation and API surface.
- +Human-in-the-loop review flow tied to detection confidence improves alarm verification quality
- +Event-based outputs support incident escalation workflows in security operations centers
- +API and automation surface reduces manual work for integration into existing monitoring stacks
- +Configurable detection thresholds help manage false positive rate versus detection latency tradeoffs
- –Onboarding is slower when camera feeds require extensive RTSP or ONVIF adjustments
- –Governance controls for multi-team routing and audit trails may need extra process design
Best for: Fits when teams need review-driven firearm detection events that feed incident escalation in a central monitoring workflow.
ZeroEyes
enterpriseAI video analytics identify visible firearms and route alerts for human verification.
Alert workflow that couples confidence-scored firearm events with guided operator verification to reduce escalation on uncertain detections.
ZeroEyes performs real-time firearm detection on live video streams and generates alert events for operator review. Its computer vision workflow emphasizes firearm classification and confidence scoring to reduce noise during monitoring.
The system supports integrations with security camera ecosystems and operational tooling used by security teams to route incidents. A key strength is the combination of automated detection with a human-in-the-loop review path for alarm verification.
- +Real-time firearm classification events with confidence scoring for triage
- +Human-in-the-loop review path supports alarm verification workflows
- +Designed for central monitoring with alert routing into security operations
- +Operational focus on lowering false positive rate versus basic motion triggers
- –Camera onboarding can require careful viewing-angle and lighting validation
- –Operational tuning is needed to balance detection latency and missed shots
- –Advanced automation relies on integration depth beyond native dashboards
- –Exporting audit artifacts for external compliance workflows can be limited
Best for: Fits when security teams need real-time alerts plus operator review to verify firearm incidents.
SoundThinking ShotSpotter
vertical specialistAcoustic sensors and software identify and locate suspected gunfire.
Case-centered incident workflow that standardizes human-in-the-loop review and escalation across responder teams.
SoundThinking ShotSpotter is a gun detection solution built around distributed acoustic sensing and a dispatch workflow. It focuses on real-time alerting that routes incidents to review teams for confirmation and escalation.
The system supports coverage planning across monitored areas and structured incident handling for security operations. ShotSpotter is designed for environments that need frequent alert throughput with operational governance for responders.
- +Acoustic detection workflow tailored for fast incident notification and dispatch
- +Incident case structure supports consistent review and escalation across shifts
- +Coverage-oriented deployment supports monitoring area planning for operations
- +Operational reporting supports management visibility into alert outcomes
- –Acoustic sensing setup can require discipline to maintain stable detection performance
- –Video analytics workflows and camera tuning are not the primary path
- –Actioning beyond alerting depends on integration with local security processes
- –False positive management needs process tuning during early rollouts
Best for: Fits when security teams need fast acoustic gun detection alerts with structured review and escalation.
Athena Security
vertical specialistVideo analytics identify weapons and other security threats in monitored environments.
Operational workflow configuration that ties firearm detection outputs to human review steps and escalation logic.
Athena Security focuses on firearm detection workflows that connect detection events to operational review and escalation. The product is built around computer vision for firearm identification, with event metadata designed for investigation.
Detection performance depends on how cameras are integrated and how confidence thresholds feed downstream actions. Admin controls are aimed at keeping incident handling consistent across sites through configurable operational rules.
- +Event metadata supports review-focused incident handling pipelines
- +Configurable detection confidence thresholds reduce obvious alert noise
- +Workflow rules help enforce consistent escalation paths across sites
- +Integration support for common IP camera and video management setups
- –Initial camera onboarding can require careful stream and layout validation
- –Alert routing and tuning need governance discipline across multiple operators
- –Real-time throughput depends on site hardware and video stream settings
- –Documentation depth varies for advanced automation and edge deployment patterns
Best for: Fits when security teams need firearm incident review and escalation automation across multiple cameras.
Scylla AI
enterpriseAI video analytics detect firearms, weapons, and other incidents from surveillance feeds.
Detection outputs include classification context and detection confidence to support review-first alerting and escalation rules.
Scylla AI is a gun detection software offering built for firearm classification and detection workflows from live video streams. It focuses on operational review loops where detection outputs can be reviewed and acted on rather than treated as a single pass fail signal.
The solution centers on integrating camera feeds and routing detection results into incident handling pipelines for central monitoring use cases. Scylla AI is designed to support ongoing tuning of detection behavior to manage detection confidence and downstream alert quality.
- +Provides firearm classification signals for incident triage
- +Supports human-in-the-loop review workflows for detection outputs
- +Integrates camera video feeds for continuous monitoring workflows
- +Emits detection confidence to guide alert handling policies
- –Operational setup requires careful tuning to control false alarms
- –Limited visibility into per-camera performance metrics
- –Automation controls depend on integration work rather than native tooling
- –Governance tooling for multi-site deployments is not extensive
Best for: Fits when security teams need configurable review and escalation around gun detection events.
Ambient.ai
enterpriseComputer vision analyzes camera feeds for weapons and security incidents.
Confidence-scored incident generation that supports rapid analyst review for firearm classification events.
Ambient.ai performs firearm detection and classification on video streams to produce event-level alerts for security workflows. It focuses on turning computer vision outputs into operational signals like confidence-scored detections and review-ready incidents.
Its core capability centers on integrating with existing camera and monitoring setups so alarms can be triggered with manageable verification steps. The main differentiator is the emphasis on detection-to-review automation that reduces manual triage during high camera throughput.
- +Event-centric alerting that attaches classification confidence to detections
- +Human-in-the-loop review workflow supports faster analyst verification
- +Automation oriented around incident creation and follow-on escalation
- +Designed for operational handling of multiple camera feeds
- –Deployment requires careful per-camera tuning to manage false positives
- –Limited visibility into model behavior beyond confidence and event outputs
- –Integration depth depends on how the video source connects to the pipeline
- –Event routing customization can demand engineering time
Best for: Fits when security teams need firearm event alerts with review workflow automation across many camera angles.
Xtract One
vertical specialistWeapons screening systems detect concealed firearms and other threats at entry points.
Confidence-scored firearm detections packaged for incident escalation, reducing manual re-check time during high event volumes.
Xtract One is a gun detection software offering focused on automated firearm detection workflows from captured video feeds. Core capabilities center on firearm detection with confidence-scored results and review-ready outputs for security teams and incident handling.
The system is positioned for integration into monitoring operations where events need to route into alerting and escalation steps. Deployment flexibility supports both on-prem and hybrid environments where camera sources are connected through common video feed interfaces.
- +Event outputs include confidence scores for faster triage
- +Supports on-prem and hybrid deployment patterns for sensitive sites
- +Designed for operational incident escalation workflows
- +Integrates with IP camera video feeds for lower routing friction
- –False-positive tuning can require repeated camera-specific adjustments
- –Admin controls are less granular than enterprise VMS governance workflows
- –Complex camera onboarding can slow initial coverage expansion
- –Workflow automation depth depends on integration configuration
Best for: Fits when security teams need confidence-scored firearm alerts and human review within existing monitoring operations.
Conclusion
After evaluating 10 public safety crime, Omnilert Gun Detection stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right gun detection software
This buyer’s guide covers gun detection software built for visual firearm detection and incident workflows using tools like Omnilert Gun Detection, Panic Technology Gun Detection, and IntelliSee. It also compares options that center on confidence-aware routing, operator review loops, and dispatch-style case handling such as Vaidio, ZeroEyes, and SoundThinking ShotSpotter.
The guide is structured around evaluation criteria and decision paths that security teams use to match each tool to real camera environments and monitoring operations. It includes common failure patterns tied to camera coverage, lighting, onboarding effort, and throughput limits seen across Athena Security, Scylla AI, Ambient.ai, and Xtract One.
Firearm detection video analytics that generate review-ready incidents and escalation events
Gun detection software uses computer vision on IP camera video streams to flag visible firearms, attach classification context, and route results into human review and incident escalation workflows. The core operational problem is turning continuous camera feeds into a manageable set of firearm-related events with evidence and clear operator next steps.
Some tools, such as Omnilert Gun Detection and Panic Technology Gun Detection, emphasize detection-to-incident handling records that keep operator confirmation and escalation outcomes together. Other tools, such as IntelliSee, focus on investigation-first review workflows that connect detections to evidence clips for analyst decisions inside existing security operations center operations.
Evaluation criteria that map to detection reliability and operator incident handling
Gun detection outcomes depend on more than model accuracy. Camera coverage, occlusion, lighting, stream quality, and tuning discipline directly change alert volume and verification speed.
The features that matter most across Omnilert Gun Detection, Vaidio, and ZeroEyes are those that control review quality, reduce false positives, and drive predictable escalation outcomes across shifts and sites.
Incident-first workflow that binds detection to operator review and escalation outcomes
Omnilert Gun Detection links each firearm event to operator review and escalation outcomes within the same handling record. SoundThinking ShotSpotter also uses a case-centered workflow to standardize human-in-the-loop review and escalation across responder teams.
Confidence-aware firearm classification routing for review and escalation
Vaidio ties each firearm classification event to downstream escalation decisions using detection confidence. Scylla AI and Ambient.ai also emit confidence signals to guide review-first alert handling and reduce manual triage.
Investigation-first evidence packaging for faster analyst decisions
IntelliSee focuses on investigation-first human review that ties detections to on-demand evidence clips. This reduces the time analysts spend jumping between screens to validate firearm presence before escalation.
Guided operator verification designed to reduce uncertain escalations
ZeroEyes couples confidence-scored firearm events with guided operator verification to reduce escalation on uncertain detections. Panic Technology Gun Detection also couples firearm classification with human-in-the-loop review before incident escalation to reduce alert noise.
Operational onboarding support for IP camera feeds and VMS handoffs
IntelliSee integrates around existing VMS workflows so alerts and evidence can move into analyst investigations. Vaidio and Athena Security both route detection outputs into central monitoring processes that depend on correct RTSP and ONVIF adjustments.
Throughput behavior under concurrent camera feeds
Panic Technology Gun Detection notes that throughput can be constrained by the number of concurrent feeds. Athena Security and Scylla AI also connect real-time throughput to site hardware and video stream settings, which affects latency and missed-shot outcomes.
Match detection-to-escalation workflow shape to camera reality and operational governance
Selection should start from how incidents must be handled once a firearm is suspected. Omnilert Gun Detection and SoundThinking ShotSpotter fit when incident records must stay consistent across shifts with clear review and escalation outcomes.
Next, selection should account for how the tool will be tuned and governed in daily operations. Vaidio and ZeroEyes handle confidence-aware review routing, while IntelliSee emphasizes evidence-first investigations tied to VMS handoffs.
Decide whether incidents must be case-centered or detection-event-centered
Choose Omnilert Gun Detection when a firearm event must connect directly to operator confirmation and escalation outcomes inside one handling record. Choose SoundThinking ShotSpotter when case structure must standardize human-in-the-loop review and escalation across responder teams.
Pick the tool philosophy that matches analyst verification time constraints
Choose IntelliSee when analyst decisions require on-demand evidence clips tied to each detection event. Choose ZeroEyes when operators need guided verification that uses confidence scoring to reduce escalations on uncertain detections.
Select based on how confidence drives your escalation logic
Choose Vaidio when escalation decisions must be driven by confidence-aware human review routing linked to firearm classification events. Choose Scylla AI or Ambient.ai when confidence context needs to support review-first alerting rules for triage at higher camera volumes.
Validate camera onboarding expectations against the environment
Choose Vaidio or Athena Security when RTSP and ONVIF adjustments are feasible for the installed camera network and monitoring setup. Choose Omnilert Gun Detection, Panic Technology Gun Detection, or ZeroEyes only if camera coverage and lighting validation can be repeated because accuracy drops with partial occlusion and false alarm rates depend on coverage and lighting.
Plan for governance and tuning discipline across multi-operator workflows
Choose Panic Technology Gun Detection or IntelliSee when advanced tuning requires operational discipline and repeatable validation for alert quality. Choose Athena Security or Scylla AI when multi-site escalation needs configurable confidence thresholds and workflow rules, and expect governance discipline for routing quality across operators.
Check whether the workflow stays effective at your concurrent feed count
Choose tools like Panic Technology Gun Detection with known throughput constraints in mind when many feeds run concurrently. Choose ZeroEyes or Athena Security and validate performance behavior using the specific camera stream settings at the intended site hardware level to control detection latency and missed shots.
Organizations that need firearm detection with operator review and escalation pipelines
Gun detection software is typically adopted by security operations centers that must reduce false alarms while still enabling fast incident response. Tools are chosen based on whether evidence packaging, confidence-aware routing, or case-centered escalation is the operational priority.
Teams also choose based on camera environment constraints like occlusion and lighting, because several tools report alert quality tied to coverage and illumination conditions. The result is that some tools fit camera-network monitoring, while others fit dispatch-style incident operations.
Security operations teams that standardize detection-to-incident handling across many cameras
Omnilert Gun Detection fits this segment because it creates an incident-first workflow that links each firearm event to operator review and escalation outcomes within the same handling record. Athena Security also fits when configurable escalation rules and confidence thresholds must enforce consistent handling across sites.
SOC teams that need classification plus review before escalation
Panic Technology Gun Detection fits when firearm classification must couple with human-in-the-loop review to reduce alert noise before incident escalation. ZeroEyes fits when confidence-scored events require guided operator verification to reduce escalations on uncertain detections.
Analyst teams that depend on evidence clips for investigation speed inside existing VMS workflows
IntelliSee fits because investigation-first human review ties detection events to on-demand evidence clips for faster analyst decisions. Vaidio also fits this operational model when detection confidence drives which downstream escalations get triggered after review.
Operations with fast dispatch throughput and structured review across responder teams
SoundThinking ShotSpotter fits when incident throughput requires case-centered review and dispatch workflow standardization. This segment benefits from the structured incident handling and operational reporting it provides across shifts.
Sites needing confidence-scored incident generation with review workflow automation
Ambient.ai fits when event-centric alerts attach classification confidence for faster analyst verification during high camera throughput. Xtract One fits when on-prem or hybrid deployments require confidence-scored firearm detections routed into incident escalation workflows.
Pitfalls that cause runaway alerts or unusable escalation workflows
Several gun detection tools show that false positives and missed detections often come from operational setup, not just model choice. Camera coverage, viewing angles, and lighting validation repeatedly determine alert quality across the list.
Another recurring pitfall is treating detection output as an end state instead of designing operator review governance and escalation rules. Tools that produce confidence and evidence still require consistent workflow configuration to avoid low-quality incident outcomes.
Ignoring occlusion and lighting constraints during rollout validation
Omnilert Gun Detection and Panic Technology Gun Detection both report accuracy drops and alert noise tied to partial occlusion and lighting. A practical corrective step is to validate coverage and illumination on each camera angle before expanding incident routing beyond initial pilot sites.
Treating detection events as sufficient without defining operator review and escalation outcomes
Omnilert Gun Detection states limited benefit when response procedures are undefined, even if detection and alerts are accurate. Athena Security and Scylla AI also require workflow rules and escalation configuration discipline so confidence-threshold logic does not route incidents into unusable states.
Underestimating onboarding work needed for camera and VMS integration
Vaidio reports slower onboarding when RTSP or ONVIF adjustments require extensive changes, and IntelliSee integration effort rises when environments lack standardized VMS workflows. Xtract One also notes complex camera onboarding can slow initial coverage expansion.
Skipping throughput planning for concurrent feeds
Panic Technology Gun Detection can constrain throughput based on the number of concurrent feeds, and Athena Security ties real-time throughput to site hardware and video stream settings. A corrective step is to test detection latency and missed outcomes using the intended stream settings before finalizing alert routing policies.
Running advanced tuning without operational discipline and governance checks
Panic Technology Gun Detection and IntelliSee both describe alert quality as dependent on camera coverage and lighting and require advanced tuning discipline. Vaidio also points to governance controls and audit trail routing needing extra process design for multi-team incident handling.
How We Selected and Ranked These Tools
We evaluated each gun detection tool on features that affect incident handling quality, ease of use for operators and admins, and value for security teams integrating firearm detection into existing workflows. Overall rating was produced as a weighted average where features carried the most weight and ease of use and value carried equal weight. This guide focuses on criteria-based editorial scoring from the provided capabilities such as review workflow design, confidence-aware routing, evidence-first investigation, incident case structure, and operational onboarding behavior.
Omnilert Gun Detection separated itself from lower-ranked tools by combining an incident-first workflow with operator review and escalation outcomes stored in the same handling record. That design lifted the features factor because it ties detection events to confirmation and escalation outcomes, which reduces the gap between alert generation and incident decision making.
Frequently Asked Questions About gun detection software
Which gun detection platforms provide an API for detection event automation into SOC workflows?
How does human-in-the-loop review differ across ZeroEyes, Panic Technology, and IntelliSee?
When do incident records get created, and how are they linked to follow-up actions?
What breaks if video management system handoffs are inconsistent in IntelliSee and Omnilert Gun Detection deployments?
Which tools are designed to reduce manual triage when camera throughput is high?
How do confidence thresholds change false positive rate versus escalation speed?
Which platforms support hybrid deployment patterns for camera sources?
What security controls exist for keeping incident handling consistent across multiple sites?
What does a typical onboarding workflow look like for connecting IP cameras and review steps in Vaidio and Ambient.ai?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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