White Paper

Build a High-Impact Loss Prevention (LP) Team: Clear roles and workflows to accelerate theft investigations and boost compliance.

Real-Time Theft Detection with AI: Facial recognition + behavioral analytics to catch store threats before they escalate.

4-Stage Theft Investigation Framework: A step-by-step approach to identify, track, and resolve organized retail crime (ORC) and shoplifting.

A CMMI-Based Strategy to Detect and Deter Shoplifting and Organized Retail Crime

CMMI + AI Video Analytics Roadmap for Loss Prevention: From manual, reactive processes — to automated, facial recognition–driven theft prevention with Capability Maturity Model Integration (CMMI).

Proven ROI with AI Video Analytics: See how one nationwide retail chain reduced theft by 50% in 12 months using AI video analytics across 183 stores.

For Retail Operations Managers – Drive store performance by integrating AI video analytics into loss prevention operations, speeding up theft investigations, and improving staff coordination in stores.

For VPs / Directors of Loss Prevention – Build a stronger LP team and use a proven investigation framework with a CMMI approach to fight theft with AI across your retail chain.

For Store Managers – Spot in-store threats faster, reduce shrink, and resolve incidents more efficiently with facial recognition in your investigation workflows.

For IT Directors in Retail Chains – Automate manual LP and theft investigation workflows by deploying scalable, secure video analytics across multiple stores.

For Security and Risk Managers – Strengthen security workflows, reduce theft risks, and move from reactive to proactive threat detection scenarios.