Platform
The foundation of Occivue’s AI ecosystem — a modular edge-to-cloud architecture that enables seamless deployment across cameras, networks, and sites while ensuring real-time decision-making with Intelligent Decision-Making Reasoning (IDMR).
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The foundation of Occivue’s AI ecosystem — a modular edge-to-cloud architecture that enables seamless deployment across cameras, networks, and sites while ensuring real-time decision-making with Intelligent Decision-Making Reasoning (IDMR).
An advanced fire and smoke detection system that leverages AI-powered visual analysis to identify early-stage fires and eliminate false alarms through contextual reasoning.
Real-time flood and leak detection powered by computer vision. Monitors water accumulation and drainage performance using temporal analytics to predict risks before escalation.
Privacy-first facial recognition built for secure access control and workforce analytics. Performs intelligent identification on-device without large-scale data storage.
AI-powered motion and performance tracking for athletes. Delivers real-time feedback, automated highlights, and performance insights for coaches and teams.
Modular plug-in system, REST/WebSocket APIs, and IDMR reasoning engine for real-time analytics. Provides audit trails, security compliance, and adaptive scalability across industries.
High-precision visual recognition for flame and smoke patterns. Integrates easily with building alarm systems, IoT devices, and emergency dispatch workflows.
Advanced water-surface segmentation and predictive alerting. Works in low-light and outdoor environments, optimized for municipal and insurance applications.
Performs facial verification and re-identification with high accuracy while maintaining privacy via on-device processing and adaptive local model training.
Offers frame-level analysis of movement, precision timing, and motion segmentation to support data-driven training and scouting decisions.
99.8% uptime, <250ms latency per event, supports up to 500 concurrent streams with automatic scaling across multi-node environments.
98.9% precision on industrial datasets, 90% reduction in false alarms compared to legacy sensors, median detection time <2s.
Detects leaks and pooling with 97% recall, predictive alerts delivered up to 5 minutes earlier than standard sensors.
99.2% accuracy at 1:1 verification, compliant with GDPR and local privacy regulations. Processes 30+ FPS on edge devices.
Real-time tracking at 60 FPS, sub-second event recognition, and 95% accuracy on action classification benchmarks.