Built for Enterprise-Scale Edge AI Deployments. Depctor AI is designed as a modern edge-first AI video analytics platform optimized for operational scalability, privacy-sensitive deployments, and multi-site enterprise management.
Unlike traditional cloud surveillance platforms that continuously upload video to centralized servers, Depctor AI performs AI processing locally at the edge. This provides reduced latency, lower bandwidth usage, improved privacy, and better resilience.
Existing RTSP and ONVIF-compatible CCTV cameras (Hikvision, Dahua, Axis, Bosch, CP Plus) stream video feeds into the Depctor edge device.
The edge device performs video decoding, object detection, multi-object tracking, face recognition, and event analysis locally using Hailo hardware acceleration.
The edge device stores detection events, tracking metadata, analytics statistics, face embeddings, and alert logs locally.
Only lightweight metadata synchronizes securely to centralized dashboards. Video footage remains local unless explicitly accessed.
The object detection stack includes YOLO-based inference models, Hailo hardware acceleration, multi-object tracking, zone filtering, and event scheduling.
Enterprise-grade face recognition workflows optimized for operational intelligence. Includes face detection, embedding generation, identity matching, and demographic estimation.
Advanced stabilization mechanisms including embedding aggregation, Top-K disambiguation, adaptive thresholds, and tracker memory optimization to significantly improve repeat visitor accuracy.
Supports enterprise multi-tenant deployments. Hierarchy includes Super Admin, Organization, Branch, Camera, and User role. Role-based permissions enable secure operational segmentation.
Edge Device Architecture: Typical edge deployments use Raspberry Pi 5, Hailo AI HAT+, Ubuntu Server, Docker containers, Local SSD storage, MariaDB, and MQTT communication.
Security is a core platform design principle. Depctor AI includes HTTPS/TLS encryption for all dashboard communication.
Depctor AI supports integration with CRM systems, ERP platforms, POS systems, BI dashboards, Webhooks, REST APIs, and MQTT systems. This enables AI analytics to become part of broader enterprise operational workflows, scaling from a single site to hundreds of locations.
