Augur provides a perception engine that transforms existing CCTV cameras into an AI‑driven monitoring platform. By delivering real‑time threat detection, anomaly analysis, and retrospective review, it enables operators of stadiums, critical national infrastructure, and other high‑risk sites to prevent incidents, cut operational costs, and extract additional value from their current camera assets.
Funding
Funding not disclosed
Founders
Product
Problem
Many organizations rely on extensive CCTV camera networks that are underutilized, providing only passive video feeds without actionable intelligence. This limits the ability of security teams in venues such as stadiums, critical infrastructure, and public spaces to detect threats, respond to incidents promptly, and derive operational insights.
Solution
Augur offers a perception engine that converts existing CCTV installations into an AI‑driven security platform. The engine processes video streams in real time to identify threats, anomalous behavior, and safety events, while also supporting retrospective analysis for investigations. By leveraging the current camera infrastructure, the solution reduces the need for additional hardware and lowers operational costs. It delivers domain‑specific outcomes—such as crowd surge detection for stadiums, perimeter monitoring for critical infrastructure, and dwell‑time heatmaps for retail—through a single, privacy‑first platform that anonymizes data by default and complies with GDPR. The platform can be deployed on‑premises or in the cloud, providing flexible integration with existing security workflows.
Target Audience
Primary customers are security and operations teams in stadiums, critical national infrastructure, mining and energy sites, transportation hubs, and large retail or mall complexes that already operate CCTV networks.
Features
- Real‑time AI threat detection and anomaly analysis across all connected cameras
- Retrospective video analytics for post‑event investigation and evidence gathering
- Domain‑specific modules (crowd surge, flare tracking, loitering detection, dwell‑time heatmaps, etc.)
- Privacy‑first architecture with default anonymization and no facial‑recognition requirement
- GDPR‑compliant video analytics and data handling
- Flexible deployment options (on‑premises or cloud) to fit existing security infrastructure