Our system is a privacy-first, on-premises edge platform designed to provide real-time, anonymous people flow analytics using existing camera infrastructure. It enables actionable insights while fully adhering to privacy-by-design principles.
Our system uses a compact edge device that connects directly to cameras and processes all data locally. Key capabilities include: Detection, tracking, and anonymization of individuals using advanced computer vision; Real-time processing with high accuracy in dense environments; Generation of anonymized metadata only, with no video leaving the premises; Analytics such as dwell time, heatmaps, queues, movement paths, group behavior, and occupancy; Integration with dashboards, reporting tools, and open APIs for further analysis.
Development followed a structured R&D process: Model training and validation under diverse environmental conditions; Optimization for edge devices to support multi-camera real-time processing; Implementation of user-friendly visualization and reporting interfaces; Mitigation of deployment complexity through standard procedures and early-stage integration.
Our system introduces a new way of understanding visitor behavior: real-time, privacy-conscious analytics that turn existing infrastructure into actionable insights. It bridges the gap between raw sensor data and operational intelligence, securely, ethically, and at scale.