Streamline your stores’ shrinkage with real-time detection of suspicious gestures linked to shoplifting

Store employee monitoring a thief using a tablet, with security camera and loss reduction graph.
Store employee monitoring a thief using a tablet, with security camera and loss reduction graph.

Table of Contents

🔍 A new era for loss prevention through AI-powered anti-shoplifting technology

Loss prevention is a key concern for managers of store chains, particularly in the grocery, DIY, or pharmacy sectors. As shopping behaviours change and shrinkage rises, traditional security solutions are showing their limits. This is where technology for detecting suspicious gestures using AI-based video analysis comes in—an innovative tool transforming loss prevention into a proactive and intelligent approach. By analysing at-risk behaviours in real time via dedicated servers and AI algorithms, this solution detects anomalies.

This anti-shoplifting technology does more than spot proven theft: it also identifies ambiguous or recurring gestures associated with shoplifting. This allows security teams to intervene more effectively, without disrupting the customer shopping experience. By targeting relevant situations, the detection system optimizes human resources and reduces losses.

For managers, this means gaining better control over shrinkage losses and return on investment through automation. A technology that combines economic performance and operational efficiency.


📊 Streamlining internal processes and data-driven decision-making

Beyond security, the detection of suspicious gestures contributes to an overall rationalization of operations. By continuously collecting data, intelligent solutions like those provided by Oxania offer unprecedented visibility into in-store dynamics. Managers can identify sensitive areas, adjust customer flows, redeploy teams, and improve shelf layouts to reduce opportunities for theft.

This not only strengthens loss prevention, but also optimizes labor costs and refines merchandising strategies. Leaders have concrete tools to make informed decisions based on real data, not assumptions. Technology becomes a real asset for day-to-day store management.

This data-driven approach also makes it possible to set more relevant security KPIs and to track their evolution over time, ensuring agile and adaptive management of prevention strategy.


🤝 A better customer experience through discreet and effective security

One of the major strengths of intelligent detection solutions is their discretion. Unlike intrusive methods like bag checks or constant visible surveillance, gesture analysis technology works in the background. It enhances security without affecting the store’s atmosphere.

For store chains that focus on customer loyalty, this is a major competitive advantage. By protecting assets without compromising the shopping experience, the solution avoids tension and inconvenience for customers, while maintaining constant vigilance over suspicious behaviors.

In short, security becomes an invisible but essential part of the customer journey, supporting brand image and contributing to a calm environment.


🚀 Oxania: a strategic partner for retail decision-makers

Executives at the head of retail chains know that it is no longer enough to react: it is necessary to anticipate. By integrating a solution such as Oxania’s, they gain a strategic tool capable of evolving their loss management model towards greater accuracy, agility, and intelligence.

Oxania combines technological expertise in computer vision with an in-depth understanding of retail challenges, offering a solution tailored for the complex environments of large stores, pharmacies, and DIY shops. Easily integrated into existing systems, this technology adapts to the specific needs of each company while ensuring measurable results.

Thanks to Oxania, anti-shoplifting technology becomes a real accelerator of operational performance, a valuable asset for streamlining resources, improving customer satisfaction, and securing revenue for the long term.

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