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SecurityTop 9 Best AI Video Surveillance Software of 2026
Compare ai video surveillance software options, including Cathexis, OpenEye, and Viseum, with tradeoffs for security teams choosing tools for coverage.
How we ranked these tools
Gitnux editors write the brief first: the topic, the inclusion rules, and the frame for what belongs.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Cathexis is the best overall pick for multi-site operators because CathexisVision brings surveillance, analytics, and third-party event data into one configurable operational interface with local recording for retention-heavy sites, whereas Deep Sentinel suits homes or small sites thanks to Live Guard response that turns AI alerts into verified warnings, sirens, and escalation.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Cathexis
CathexisVision combines surveillance, analytics, access control, and third-party system events inside one configurable operational interface.
Best for: Fits when multi-site operators need local video control, integrated analytics, and connections to existing security systems.
OpenEye
Editor pickOpenEye Web Services unifies locally recorded video from distributed sites under centralized browser-based monitoring and administration.
Best for: Fits when organizations need local video retention, centralized oversight, and consistent administration across multiple sites.
Viseum
Editor pickViseum’s AI threat assessment engine prioritizes suspicious activity across multiple camera views for coordinated operator response.
Best for: Fits when security operators need automated threat assessment across large, distributed camera networks.
Comparison Table
Cathexis
enterpriseVideo management software with AI analytics and behavior recognition.
CathexisVision combines surveillance, analytics, access control, and third-party system events inside one configurable operational interface.
Cathexis provides desktop and web interfaces for live viewing, playback, alarm handling, reporting, and system administration. CathexisVision supports integrations with cameras, access control systems, point-of-sale systems, building management equipment, and external data sources. Its analytics library includes object classification, people counting, license plate recognition, facial recognition, direction analysis, and behavior-related detection options.
The main tradeoff is configuration complexity across analytics, integrations, permissions, and multi-site deployments. Cathexis fits transport facilities, retail estates, campuses, and industrial sites that need local recording with centralized investigation. Its modular architecture also allows operators to connect specialized systems instead of replacing every existing security component.
- +Broad integrations for cameras, access control, point-of-sale, and building systems
- +Local recording supports sites with strict retention and connectivity requirements
- +Analytics cover people, vehicles, license plates, and perimeter events
- +Central administration supports multi-site surveillance operations
- –Advanced deployments require substantial planning and configuration
- –Some analytics depend on compatible cameras or separately licensed modules
- –Interface complexity can slow onboarding for small security teams
- –Cloud-first teams may prefer a more remote-native architecture
Multi-site security teams
Centralized incident investigation
Faster cross-site investigations
Retail security departments
Point-of-sale video correlation
Stronger transaction evidence
Show 2 more scenarios
Transport operators
Perimeter and vehicle monitoring
Earlier perimeter response
Analytics flag vehicle activity, restricted-area entry, and selected movement patterns around transport infrastructure.
Industrial facility managers
Local recording and alarms
Unified site oversight
Facilities retain footage locally while coordinating camera alarms with access control and building equipment.
Best for: Fits when multi-site operators need local video control, integrated analytics, and connections to existing security systems.
OpenEye
enterpriseVideo surveillance software combines cloud-managed recording, video management, monitoring, and AI search.
OpenEye Web Services unifies locally recorded video from distributed sites under centralized browser-based monitoring and administration.
OpenEye combines network video recording with cloud-managed surveillance through its OpenEye Web Services architecture. The system supports live viewing, forensic search, video export, health monitoring, and centralized administration across distributed sites.
OpenEye's analytics can identify people and vehicles, while integrations connect cameras, access control, alarms, and third-party systems. Its strongest use case is multi-site security operations that need local recording with browser-based oversight.
- +Hybrid architecture keeps recording local while enabling centralized browser access.
- +OpenEye Web Services supports multi-site monitoring and administration.
- +AI analytics provide person and vehicle detection for event review.
- +Integrations cover access control, alarms, cameras, and business systems.
- –Advanced analytics and integrations can require additional configuration.
- –Hardware and deployment choices create more planning work than cloud-only systems.
- –API and automation documentation is less visible than the main management workflows.
- –Smaller sites may not need the full multi-site feature set.
Security operations center managers
Coordinating alerts across multiple sites
Faster incident triage and coordination
Investigators and forensic analysts
Searching incidents using AI signals
Reduced time to find evidence
Show 2 more scenarios
Facility security administrators
Managing recording and access events
Unified event correlation and reporting
Integrations connect cameras, access control, and alarms for consistent operational logging and exports.
IT and systems integrators
Deploying browser-based site oversight
Lower operational management overhead
OpenEye Web Services supports centralized administration while keeping local recording for each site.
Best for: Fits when organizations need local video retention, centralized oversight, and consistent administration across multiple sites.
Viseum
enterpriseAI video surveillance with multi-camera tracking and situational awareness.
Viseum’s AI threat assessment engine prioritizes suspicious activity across multiple camera views for coordinated operator response.
AI video surveillance increasingly depends on analytics that can interpret events across large camera networks, and Viseum focuses on that operational layer. Its platform combines AI-based detection, automated threat assessment, and real-time alerts for perimeter, site, and public-space monitoring.
Viseum supports integration with existing CCTV infrastructure, helping security teams coordinate video intelligence without replacing every camera. The main limitation is that advanced deployments require careful system design, camera calibration, and operational governance.
- +AI threat assessment helps prioritize events instead of presenting every detection equally
- +Supports large-scale camera deployments across sites with different surveillance requirements
- +Integrates analytics with existing CCTV and security operations workflows
- +Automated detection can reduce dependence on continuous manual monitoring
- –Deployment typically needs specialist configuration and site-specific calibration
- –Public documentation provides limited detail about API endpoints and automation workflows
- –User experience depends heavily on the surrounding CCTV and command-center setup
- –Advanced analytics may require compatible cameras, infrastructure, and integration work
Perimeter security operations teams
Detect intrusions along site boundaries
Fewer missed intrusion events
Security managers at logistics hubs
Monitor yard movement and staging areas
Faster incident response
Show 2 more scenarios
Public space security coordinators
Flag suspicious behavior in transit areas
Quicker escalation to authorities
Viseum provides automated detection and assessment workflows for public-space surveillance using existing camera setups.
Corporate risk and compliance leads
Govern AI alerts across multiple sites
Consistent security operations
Viseum helps standardize operational handling of AI video events across heterogeneous camera infrastructure.
Best for: Fits when security operators need automated threat assessment across large, distributed camera networks.
C2P
enterpriseAI video surveillance platform for threat detection and situational awareness.
Centralized operational video intelligence that turns distributed camera activity into prioritized security incidents.
C2P supports centralized oversight of video security operations across multiple locations. Security teams can review camera activity, investigate detected incidents, and organize responses from a shared interface. The product fits environments where recurring visual events require consistent handling by internal teams or monitoring personnel.
- +Centralizes video security operations across distributed locations
- +Prioritizes detected incidents for faster operator review
- +Supports structured investigation of live and recorded footage
- +Fits multi-site security teams with recurring event workflows
- –Detection quality depends on camera placement and scene conditions
- –Initial configuration requires defined event policies and response procedures
- –Advanced workflows may require integration and administrative planning
- –Local teams may need training for centralized incident handling
Best for: Fits when distributed security teams need centralized video event review and coordinated incident response.
Deep Sentinel
vertical specialistAI-powered video surveillance combines camera detection with live security intervention for monitored sites.
Live Guard response links AI camera alerts to verified audio warnings, sirens, lights, and emergency escalation.
Residential and small commercial sites needing human-reviewed intervention fit Deep Sentinel best, especially when cameras must trigger live security responses. Its Sentinel AI analyzes camera feeds for people, vehicles, and activity, while trained guards can verify events and communicate through the system.
- +Live Guard intervention adds human verification after AI-detected activity.
- +AI cameras support person, vehicle, and unusual-activity detection.
- +Two-way audio, sirens, and lights provide active deterrence.
- +Mobile alerts and event clips support remote incident review.
- –Hardware and monitoring depend on the Deep Sentinel ecosystem.
- –Third-party camera and on-premises VMS integration are limited.
- –Advanced analytics coverage is narrower than enterprise video platforms.
- –Large multi-site deployments may require substantial operational coordination.
Best for: Fits when homes or small sites need AI detection followed by live human intervention.
ZeroEyes
vertical specialistAI video analytics software detects weapons and security threats from existing camera feeds for response teams.
Human-verified firearm detection combines computer vision alerts with analyst review before escalation.
ZeroEyes analyzes live camera feeds for firearm threats and sends verified alerts to designated responders. Its computer vision service integrates with existing video infrastructure instead of requiring a full camera replacement.
- +Firearm detection focuses the product on a clearly defined security threat.
- +Human verification helps reduce false firearm alerts before notification.
- +Integrates with existing cameras and video management systems.
- +Alerts can reach security personnel and emergency response workflows.
- –Narrower coverage than systems supporting broad behavioral and vehicle analytics.
- –Performance depends on camera positioning, image quality, and lighting.
- –Human verification introduces operational dependency during incidents.
- –Public API and granular administration details are less visible than core detection features.
Best for: Fits when organizations need firearm-focused monitoring across existing camera networks and coordinated emergency response.
Camio
SMBCloud video security software provides AI-assisted search, alerts, monitoring, and camera management.
Natural-language video search lets operators locate people, objects, and activities across large footage collections.
Camio differentiates itself through browser-based investigation across live and recorded camera feeds, with natural-language search for visual events. It supports cloud-managed cameras, existing network cameras, and integrations with systems such as Verkada, Rhombus, and Google Workspace.
- +Natural-language search reduces manual review across recorded camera footage.
- +Works with many existing IP cameras and cloud camera ecosystems.
- +Automated alerts can target people, vehicles, objects, and defined behaviors.
- +Google Workspace integration supports identity management and controlled video sharing.
- –Camera compatibility and stream setup can require technical administration.
- –Detection accuracy depends on camera placement, lighting, and scene conditions.
- –Advanced retention and alert policies require ongoing governance.
- –Native controls are less suited to organizations needing a full on-premises VMS.
Best for: Fits when security teams need searchable multi-camera footage without replacing existing camera infrastructure.
viisights
enterpriseBehavioral video intelligence software analyzes live and recorded video for safety, security, and operational events.
Viisights behavioral analytics identify activity patterns such as crowd formation, loitering, queueing, and abandoned objects.
Security teams managing distributed sites fit viisights when they need AI analysis across existing camera infrastructure. Its Viisights Video Intelligence platform applies behavioral analytics to detect activities such as crowding, intrusion, loitering, abandoned objects, and queue formation.
- +Behavioral analytics cover crowding, loitering, intrusion, and abandoned-object scenarios.
- +Supports integration with existing CCTV and video management infrastructure.
- +Real-time alerts can direct operators to defined security events.
- +Video intelligence applies to transport, retail, public-space, and enterprise monitoring.
- –Public documentation provides limited detail about API endpoints and automation workflows.
- –Advanced analytics require careful camera placement and scenario configuration.
- –Feature coverage can depend on selected deployment modules and integrations.
- –Administrative controls and audit capabilities receive less public detail than competing products.
Best for: Fits when security teams need behavioral video analytics across transport, retail, or public-space camera networks.
IpConfigure
enterpriseEnterprise video management with AI analytics and cloud or on-prem deployment.
Orchid Fusion provides centralized browser access to independently managed Orchid video systems across multiple locations.
Within AI video surveillance, IpConfigure combines an on-premises video management system with cloud-connected administration and analytics. Its Orchid platform supports live viewing, recording, camera management, investigation, and multi-site operations through a browser interface.
- +Orchid Fusion centralizes monitoring across multiple geographically separated sites.
- +Browser-based live view and investigation reduce dependence on dedicated workstation software.
- +ONVIF support accommodates mixed-camera environments and existing surveillance hardware.
- +Access-control integrations connect video events with facility entry activity.
- –Advanced analytics coverage depends on compatible cameras, licenses, and deployment modules.
- –Large installations require careful network, storage, and camera-capacity planning.
- –The interface can become complex across multi-site roles, devices, and recording policies.
- –Automation and event integrations are less extensive than API-first surveillance products.
Best for: Fits when organizations need centralized oversight for distributed sites using mixed camera infrastructure.
Conclusion
After evaluating 9 ai video surveillance software, Cathexis 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.
Frequently Asked Questions About Ai Video Surveillance Software
How do AI video surveillance tools differ in cross-camera investigation and search workflows?
Which tools fit teams that need natural-language or activity-based queries over stored footage?
What integration options matter most when video analytics must interact with access control, alarms, or building systems?
How do ONVIF and camera compatibility affect deployment planning for distributed sites?
What SSO and RBAC controls should security teams verify before onboarding analysts and administrators?
How should teams plan data migration when moving from legacy VMS to a newer AI platform?
What configuration choices most impact detection throughput and alert quality?
How do organizations handle human verification and escalation when AI detections require confirmation?
Which tools provide documented extensibility via APIs or event integration for custom automation?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Ai Video Surveillance Software
AI video surveillance options mainly differ in how tightly the platform handles model-to-camera configuration, how it turns motion and events into usable records, and how well it fits your admin workflow through RBAC and audit log coverage. Pick based on those differences, not on marketing claims.
Camera onboarding and scene rules
Why it matters
Camera onboarding and scene rules determine whether AI behavior stays consistent when lighting, angles, or layouts change. This is where teams notice drift between expected and actual detections.
How to check
During a demo, ask the vendor to walk through adding one new camera and applying the correct scene settings. Then show how the rules behave after you change time of day or upload a short test clip and re-run detection.
Typical range
unknown
Event timeline recall and review
Why it matters
Event timeline recall and review decide how quickly you can verify what the AI saw and why. In real investigations, speed matters less than correctness and traceability of the event context.
How to check
Request a sample case: a person and a vehicle entering and leaving. Verify you can jump from the event card to the exact time window and related clips without manual scrubbing.
Typical range
unknown
Retention and evidence export
Why it matters
Retention and evidence export control whether you can meet incident review timelines and keep records when you need them. Weak export workflows often force last‑minute screen captures.
How to check
Ask what happens to event clips and metadata after you set a retention window. Then test an export workflow from an event to a shareable package and confirm which fields and timestamps are included.
Typical range
unknown
API automation for events and alerts
Why it matters
API automation for events and alerts affects how much work you can remove from manual triage. If event delivery is rigid, you end up building brittle workarounds.
How to check
Ask to see the event payload structure and delivery method. Then request a small automation example: filter events by camera and time, and push results to a webhook or ticketing endpoint.
Typical range
unknown
RBAC roles and audit log coverage
Why it matters
RBAC roles and audit log coverage show whether you can delegate review without losing accountability. When investigations cross teams, missing audit trail details become a process risk.
How to check
On a demo account, create two roles with different permissions and confirm what each can view and export. Then find an example of who accessed or exported an event and verify the audit log records the action and context.
Typical range
unknown
Configuration controls for false positives
Why it matters
False-positive controls shape how often analysts waste time on non-events. The best tools give practical knobs that match your site conditions, not just overall sensitivity sliders.
How to check
Ask for a workflow to tune detections for one location with known nuisance patterns. During the demo, show how you adjust the configuration, then re-run a short clip and compare before/after event counts and the affected event types.
Typical range
unknown
Red flags
- Event review skips exact time window linkage
- Evidence export omits key timestamps or metadata
- RBAC changes don’t show up in the audit log
Fit by situation
- If you add cameras with different angles or layouts often, prioritize Camera onboarding and scene rules.
- If investigators need to move fast from alert to proof, prioritize Event timeline recall and review.
- If you have workflows that ingest alerts into other systems, prioritize API automation for events and alerts.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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