Cut checkout fraud by 30% with Smart Exception Reporting
Optimize layout and staffing using heatmaps and dwell time tracking
Prevent theft and fraud with real-time alerts
Grocery retail is evolving rapidly with the rise of self-checkout, curbside pickup, and delivery services. i3 International helps grocery operators meet these demands with an Ai-powered video analytics platform that integrates seamlessly with your existing infrastructure. We turn everyday operational data into real-time intelligence, enabling faster decision-making and measurable performance improvements.
Asset Protection
Operational Efficiency
Safety and Security
“i3’s level of service has been absolutely fantastic and their customer support is always on point and we have never had a better product in our building.”
Corey Freeman
Our platform is designed to manage complex retail environments with multiple departments, varying traffic flows, and diverse customer behaviors. Heat mapping and people counting analytics adapt to grocery-specific patterns including seasonal changes, promotional events, and department-specific traffic.
Yes. Our advanced Ai detection specifically monitors for common grocery theft methods including bottom-of-basket concealment, and self-checkout skipping. The system alerts staff in real-time to prevent losses while maintaining a positive customer experience.
Smart-ER is designed to handle high-volume environments efficiently. The system intelligently prioritizes alerts based on risk levels and transaction patterns, ensuring that your staff focuses on the most critical incidents without being overwhelmed by false positives.
Our platform provides specialized monitoring for service counters including deli, bakery, and seafood departments. Analytics help optimize staffing levels, reduce wait times, and improve service efficiency in these high-touch customer areas.
Heat mapping reveals which areas of your store generate the most customer engagement, helping you optimize promotional display placement. You can measure the effectiveness of seasonal merchandising and adjust layouts based on actual customer behavior data rather than assumptions.
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