AI Live Insight

AI Live Insight is a software-only layer that connects to existing IP cameras and VMS platforms via standard RTSP/ONVIF protocols. It receives video streams, runs AI detection in real time, and generates alerts -- without touching or replacing any installed camera hardware.

Traditional monitoring relies on human operators who fatigue and miss incidents. AI Live Insight runs 24/7 without attention gaps, detects threats in real time, and generates structured event data for accountability. Organizations reduce response times and staffing costs for monitoring rooms.

NVR/VMS systems record and play back video but do not analyze it. AI Live Insight adds AI detection, classification, alerting, and structured event records on top of existing NVR/VMS infrastructure. The system understands what is happening in the video, not just that video exists.

Camera-embedded analytics are limited by onboard processing power and locked to that vendor's ecosystem. VIDIZMO runs centralized GPU-powered AI across cameras from any manufacturer, supports custom model training, and scales independently of camera hardware refresh cycles.

No. Any IP camera or VMS supporting RTSP or ONVIF works with AI Live Insight. The platform also supports drone feeds and fleet vehicle cameras. Organizations leverage their existing camera investments without purchasing proprietary hardware.

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AI Live Insight detects multiple threat types, with each detection generating configurable alerts via email, SMS, or 311/CRM integration.

• Weapon detection (guns, knives, gunshots)
• Crowd surge and stampede conditions
• Abandoned vehicles
• Unattended objects (IED prevention)
• Trespassing
• Robbery activity

Yes. VIDIZMO fine-tunes pretrained models with customer-provided labeled data for domain-specific patterns. Organizations can also bring their own approved models or open-source models. Custom models are isolated per customer for data security.

YOLOv5/YOLOv8 architectures achieve 95% accuracy with less than 3% false positive rates on standard categories. Activity recognition achieves 92%+ accuracy. Configurable confidence thresholds let operators tune sensitivity per detection type to balance thoroughness and false positives.

AI Live Insight performs face detection (a face is present) and tracking (following across frames), not facial recognition (identifying who someone is). This distinction matters for privacy -- detection and tracking are privacy-preserving capabilities without identity matching.

AI Live Insight detects a range of municipal conditions, with all detections routing to 311/CRM systems as structured service requests.

• Copper wire theft activity
• Illegal dumping
• Road hazard and pothole detection
• Trash accumulation
• Double parking
• Bike-lane/ADA blockage
• Loading zone misuse
• Overstaying

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VIDIZMO addresses 17 transit use cases validated with Toronto TTC including fare evasion detection, platform safeguarding, crowd counting, track intrusion alerts, loitering detection, fallen person assistance, and demographic analysis for service planning.

PPE compliance detection, cycle-time analysis for production efficiency tracking, and unsafe behavior detection on factory floors. Models are fine-tuned on customer-specific manufacturing environments with real-time alerts to safety managers for immediate response.

DOT agencies use AI Live Insight for pothole detection, road hazard identification, illegal dumping monitoring, copper wire theft prevention, and infrastructure condition assessment. Detections generate structured 311 requests with location, severity, and linked video for field verification.

Yes. AI Live Insight detects double parking, bike-lane blockage, ADA zone violations, loading zone misuse, and overstaying. Each violation generates a structured event record with timestamp, location, and video evidence that can route to enforcement or municipal CRM systems.

Agencies deploy AI Live Insight for real-time surveillance with license plate recognition (ALPR/ANPR), suspect detection, activity monitoring, and weapon detection. Event-based recording captures footage around incidents for evidence preservation in the Digital Evidence Management System.

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Each AI Live Server instance handles 32 simultaneous camera streams. Scale horizontally by adding GPU server instances -- 5 cameras need one server, 100 cameras need four. Phased deployment lets organizations prove value on a small scale before expanding.

Phased deployment means rolling out incrementally -- one corridor, district, or facility at a time. This reduces upfront investment, proves ROI on a small scale, aligns with budget cycles, and lets organizations refine detection models before expanding to additional camera groups.

AI Live Insight deploys fully on-premises with no internet dependency. All AI models run locally, detections stay within the secure network, and the management interface operates without cloud connectivity for classified or high-security installations.

AI Live Insight requires GPU-equipped servers for AI processing. Organizations can use existing GPU servers or add dedicated hardware. Each server instance handles 32 camera streams, so infrastructure planning is straightforward based on camera count.

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Alert routing is configurable per detection type. Weapon detections can trigger immediate SMS to security teams, potholes generate 311 requests for public works, and PPE violations alert safety managers via email. Webhooks send structured event data to any external system.