UST Scan and Go with Vision-Powered Loss Prevention Retail Automation

UST Scan and Go with Vision-Powered Loss Prevention is an AI-driven self-checkout and retail security platform that helps retailers reduce shrink, improve operational efficiency, and deliver a frictionless customer experience. Built on AWS for scalability, resilience, and secure data processing, the solution combines mobile cart building, computer vision, behavioral analytics, and edge computing to provide real-time fraud detection without slowing down the checkout journey.

Shoppers simply scan items with their smartphones, generate a digital cart, and complete payment at a kiosk using their preferred method, including digital wallets, cards, or cash. Meanwhile, AI models running at the edge analyze every interaction for anomalies such as barcode manipulation, fake scans, mismatched items, or suspicious in-aisle behavior. This proactive approach helps retailers stop theft before the transaction is finalized, reducing shrink by up to 25% and increasing checkout efficiency by up to 30%.

All events, including potential fraud, behavioral triggers, and completed transactions, are logged and synced to AWS for auditability, analytics, and centralized oversight. Retailers can review visual evidence, drill into SKU-level data, and integrate insights with existing POS, PIM, and payment systems using SDKs and APIs.

The platform is compatible with standard packaged goods, variable-weight items, and restricted products, making it suitable for grocery, convenience, campus retail, and high-traffic multi-format stores.

UST Scan and Go enables autonomous or hybrid staffing models, supports diverse customer payment preferences, and deploys quickly across new or existing store formats, helping retailers modernize checkout, protect revenue, and improve both security and shopper satisfaction.

Key Features

• AI-based barcode validation and theft detection: Identifies fake scans, barcode swaps, mismatched items, and fraudulent behaviors before payment is completed.
• Computer vision and in-aisle behavioral analytics: Detects suspicious patterns such as repeated re-entry, prolonged loitering, or inconsistent movement that may indicate theft intent.
• App-free mobile scanning and QR-based checkout: Shoppers use their smartphones without downloading an app, enabling fast adoption and minimal friction.
• Edge-to-cloud processing on AWS: Low-latency edge inference ensures real-time fraud detection; cloud dashboards provide centralized analytics, reporting, and audit trails.
• Modular SDKs and APIs for seamless integration: Connect easily to existing POS, PIM, CRM, and payment systems without replacing current store infrastructure.
• Autonomous and hybrid deployment flexibility: Supports fully unmanned lanes, assisted kiosks, and dual-lane configurations for diverse retail operating models.
• Omnichannel payment options: Accepts digital wallets, credit/debit cards, and cash for consumer inclusivity and broad adoption.
• Comprehensive transaction video logging: Provides visual evidence of item interactions and checkout activity for compliance, dispute resolution, and training.

Key Benefits

• Reduce shrink by up to 25% with proactive fraud detection: AI identifies theft attempts in real time, enabling staff to intervene before losses occur.
• Increase checkout efficiency by up to 30%: Faster, mobile-first self-checkout reduces kiosk congestion and improves throughput in high-traffic environments.
• Improve operational control through centralized oversight: Cloud-based dashboards offer visibility into store behavior, transaction logs, and security events.
• Enhance shopper experience with frictionless, app-free checkout: Customers scan, pay, and go—minimizing wait times and eliminating unnecessary steps.
• Deploy across diverse retail formats with minimal hardware changes: Suitable for grocery, convenience, campus retail, micro-markets, and multi-format stores.
• Free up store associates for higher-value tasks: Staff can focus on customer service, replenishment, and store operations instead of manual kiosk monitoring.
• Strengthen auditability and compliance: Video-backed transaction logs provide a clear record for investigation, training, and compliance.
• Gain enterprise scalability with AWS-powered architecture: Leverage AWS for secure data processing, analytics, and integration across multi-store deployments.