UST Vision Checkout (NAYAN): AI-Powered Touchless Self-Checkout Solution

UST Vision Checkout (NAYAN) is an AI-powered, touchless self-checkout platform that merges advanced computer vision with large language models (LLMs) to deliver instant, multi-item recognition and intelligent customer engagement. Designed for high-velocity environments such as airports, cafés, cafeterias, and retail foodservice, NAYAN eliminates the need for scanning, manual input, or barcode alignment—enabling a frictionless, sub-5-second checkout journey.

Built on a vision-first, AI-native architecture, the system identifies plated meals, packaged items, and complex product combinations placed on a smart tray. Computer vision algorithms detect and classify multiple items simultaneously with high accuracy, while LLMs enrich the experience with contextual recommendations, color-coded nutrition details, and real-time insights that help increase basket value and transparency.

NAYAN processes more than 1,000 transactions per day in production environments such as Jackson Hole Airport, demonstrating its ability to maintain accuracy and speed at scale. Its edge-to-cloud design ensures low-latency inference at the point of sale, with AWS cloud connectivity supporting analytics, reporting, and multi-site management.

The platform integrates easily with existing POS, self-checkout, and order management systems through modular SDKs and APIs. Retailers can deploy Vision Checkout as a standalone smart kiosk or embed it within their broader retail automation ecosystem. With built-in support, developer documentation, and 24×7 technical assistance, NAYAN is engineered for reliability, operational efficiency, and seamless enterprise adoption.

Key Features

• Real-time, multi-item computer vision checkout: Automatically identifies multiple items on a tray—no barcodes, scanning, or manual input required.
• LLM-powered recommendations and nutrition insights: Provides intelligent upsells, complementary item suggestions, and clear nutrition transparency using generative AI.
• Touchless, sub-5-second transaction flow: Enables rapid throughput in busy foodservice environments by eliminating friction and reducing queue times.
• Edge-to-cloud deployment flexibility: Low-latency edge inference for instant recognition, with AWS-enabled cloud dashboards for analytics and oversight.
• Seamless POS/SCO integration and APIs: Connects easily with POS, self-checkout, and retail management systems through SDKs and integration toolkits.

Key Benefits

• Increase transaction speed and reduce checkout times: Touchless recognition accelerates high-volume checkout and improves customer flow.
• Improve accuracy with AI-powered multi-item detection: Computer vision reduces human error and ensures consistent item identification.
• Boost revenue with contextual, AI-driven upselling: LLMs surface complementary items and personalized suggestions to increase basket value.
• Enhance customer experience through transparency: Color-coded nutrition labeling and real-time insights help customers make informed choices.
• Reduce operational overhead in foodservice environments: Automates the checkout process, freeing staff for preparation, replenishment, and customer service.
• Deploy across diverse formats with minimal change: Works seamlessly in airports, cafés, cafeterias, corporate dining, and quick-service restaurants.
• Scale confidently with AWS-powered architecture: Edge-to-cloud intelligence supports secure data processing, reporting, and multi-location analytics.
• Integrate easily into existing POS ecosystems: SDKs and APIs enable fast deployment without disrupting current infrastructure.