Smart, efficient, anonymous People Counters & Analytics to the real world.
Our solution allows for easy deployment, capture, analysis, and reporting of the number people who enter a physical place. Optionally, we can also capture and report occupancy in real time.
We assist Retailers, Universities, Casinos, Places of Worship, Office Buildings, and other industries in analyzing and taking action on their people traffic trends.
We offer a special package for retailers to measure performance on traffic, including conversion rate and service levels. Our direct integrations make it easy to combine POS data with staff data. The Retail Equation simulator lets users run simulations to improve sales. It can also be used as a learning tool to understand how traffic, staffing, conversion rates, and quality service relate.
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Overmonitor is cloud-based infrastructure, website, and endpoint monitoring built for teams that want fast setup, clear alerts, and practical visibility without the complexity or cost of enterprise monitoring suites. Monitor websites, servers, endpoints, processes, Windows services, event logs, uptime, response time, SSL certificates, and internal network health from one easy dashboard.
At the core of Overmonitor is a small, lightweight server agent that installs quickly, pairs with your account, and reports a heartbeat every minute from inside your network. This gives you visibility beyond public uptime checks, helping detect server outages, stalled services, failing processes, internal connectivity problems, and endpoint health issues before they become customer-facing downtime.
Overmonitor supports city-level geotargeted monitoring, practical maintenance windows that reduce alert noise, push notifications for alerts, audible dashboard alerts for operations screens, process monitor rollups, embeddable performance graphs, and flexible à la carte pricing so you only pay for the monitoring you need.
Designed for SaaS operators, IT teams, MSPs, developers, and small businesses, Overmonitor helps you track availability, analyze website performance, monitor infrastructure health, and improve end-user experience without being locked into a bloated monitoring platform.
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InfiEye
AI-video analytics allows store managers to detect and prevent shrinkage as well as inventory thefts as soon as they occur. InfiEye AI can help you improve your in-store shopping experience. It can identify fast-selling SKUs on shelves and monitor customer behavior in-store. You can integrate with your existing PoE cameras in-store. Place your cameras at the points you wish to monitor. The image recognition algorithm analyzes live in-store feeds frame by frame to identify every object on the shop floor. Staff are notified by evidence-based alerts to ensure that they can intervene in a friendly way. Track sales performance and inventory stock-outs. Each store can reduce shrinkage and increase net-sales.
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Honeywell Active Alert
Honeywell Active Alert is available in three distinct tiers: base, standard, and premium, each designed to identify various behaviors. The Base package provides essential detections for individuals and vehicles, along with features like camera tamper detection, blinding, blurring, and scene change recognition. It generates real-time alerts to inform users of any alterations that might compromise the camera view due to either deliberate or accidental actions. Expanding upon the Base package, the Standard package introduces the capability to recognize more complex behaviors, including instances of individuals jumping fences or loitering, as well as vehicles that are parked or stopped off the main road. Further enhancing security capabilities, the Premium package incorporates features for detecting abandoned or removed items and potential theft situations. Collectively, Honeywell's range of video analytics solutions serves as an excellent enhancement to the existing security measures of any facility, providing comprehensive coverage and peace of mind. In today's world, ensuring safety through advanced technology is more crucial than ever.
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