UST Product Box with AI Catalogue Digitization & PIM on AWS

UST Product Box with AI Product Catalogue Digitization on AWS is an AI-powered catalogue management platform that turns physical SKUs into rich, PIM-ready product content in minutes. Built on an edge-to-cloud architecture using AWS, it digitizes packaging, extracts product attributes, and publishes schema-aligned data into PIM, DAM, ERP, and ecommerce systems so retailers and CPG brands can keep up with omnichannel growth without scaling manual work.

Using a compact vision-AI capture pod, operators place items on a turntable and capture multi-angle imagery in seconds. Computer vision, OCR, and NLP automatically extract barcodes, titles, nutrition panels, ingredient lists, regulatory text, usage instructions, and on-pack marketing claims, then map them to your catalogue or PIM taxonomy with full traceability. Typical deployments digitize 300+ SKUs per day per pod with far fewer errors than manual processes.

UST Product Box is built for PIM, DAM, ecommerce, and retail media teams that depend on complete, accurate product data to power search, recommendations, retail media, and in-store digital experiences. The AWS-based cloud layer provides workflow tracking, quality control, and analytics, while the hardware-agnostic design makes it easy to roll out capture pods across sites in under 12 weeks. Customers use the platform to accelerate content onboarding, reduce operational cost and rework, and unlock stronger first-party attribution for retail media and marketplaces.

Key Features

• Vision-AI pod for multi-angle product imaging: Captures consistent, high-resolution imagery of each SKU via a compact capture pod, enabling studio-quality product photography without dedicated photo studios.
• Computer vision, OCR, and NLP for attribute extraction: Uses computer vision, optical character recognition, and natural language processing to read packaging and automatically extract barcodes, titles, nutrition facts, ingredients, regulatory text, and marketing claims.
• Schema-aligned data output for PIM, DAM, ERP, and marketplaces: Maps extracted attributes into catalogue, PIM, DAM, and ERP schemas, producing clean, structured product data ready for ecommerce, retail media, and marketplace listings.
• Edge-to-cloud hybrid architecture on AWS: Runs capture and inference at the edge for low-latency digitization while syncing to an AWS-based cloud layer for storage, enrichment, workflow orchestration, and integration with downstream systems.
• Workflow tracking, QC, and analytics dashboard: Provides a cloud dashboard to monitor SKU throughput, validate extracted attributes, resolve exceptions, and view analytics on time-to-shelf, error rates, and catalogue completeness.
• Hardware-agnostic, remotely manageable design: Supports a setup that can be deployed in stores, warehouses, or studios, with remote monitoring, configuration, and software updates centrally managed via AWS.
• High-throughput SKU digitization with traceability: Enables teams to digitize 300+ SKUs per day per pod, with every image and attribute linked back to the original capture session for auditability.
• Enterprise deployment, support, and APIs: Includes installation support, operator training, APIs, documentation, and 24×7 support so teams can deploy quickly and maintain the platform with minimal engineering effort.

Benefits

• Accelerate time-to-shelf and channel onboarding: Replace manual content creation with automated AI product catalogue digitization to cut onboarding cycles and get new and updated SKUs live across channels faster.
• Reduce catalogue creation and maintenance costs: Lower spend on photography, data entry, and cleanup by standardizing on a single AI-powered catalogue management workflow that scales without adding headcount.
• Improve product data quality and completeness: Ensure every SKU has consistent images and accurate attributes, reducing listing errors, returns, and customer service issues.
• Unlock stronger first-party attribution and retail media ROI: Feed high-quality, structured product data into search, recommendation, and retail media systems to improve targeting, reporting, and monetization.
• Standardize catalogue workflows across banners and regions: Apply consistent taxonomy, imagery, and content standards across categories, banners, and geographies while still allowing for regional variations.
• De-risk SKU growth and channel expansion: Scale to new categories, suppliers, and marketplaces without proportional increases in manual work, using AWS scalability and automated SKU processing to absorb demand.
• Realize rapid ROI from catalogue automation: Combine faster onboarding, reduced labor, and higher-quality product data to drive measurable ROI from product catalogue digitization and PIM automation.