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Amazon uses SageMaker AI to grade A+ Content quality holistically

Amazon Marketplace is testing a new AI system to evaluate the quality of A+ Content—rich media widgets on product detail pages—by assessing the entire page as customers see it. The system combines a vision-language model (VLM) with optical character recognition (OCR) to score four dimensions: Visual Storytelling, Feature Presentation, A+ Layout, and Conversion Optimization. It also uses a…

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Key points

  • Amazon’s SageMaker AI system scores A+ Content quality by rendering pages as snapshots and using a VLM with OCR signals
  • CatBoost classifier trained on 5,478 expert-annotated pages improves accuracy over baseline scoring methods
  • SHAP explains decisions and an LLM generates actionable improvement recommendations for sellers

The system renders each page as a single snapshot, allowing the VLM to assess how individual assets interact rather than evaluating them in isolation. OCR signals—like Text Density, Character Density, and Spacing—complement the VLM’s holistic judgment, addressing fine-grained readability issues. SHAP identifies which features drive low-quality decisions, and an LLM translates those insights into specific improvement suggestions. Deployed on Amazon SageMaker AI, the pipeline supports scalable rendering, inference, and monitoring, with plans to explore lighter VLM backbones for global catalogs.

Full story from AWS Machine Learning Blog · by James Kim primary sourceOpen source ↗

How Amazon Marketplace evaluates content quality with Amazon SageMaker AI

AWS Machine Learning Blog · 5 November 2026

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This text was published by AWS Machine Learning Blog and written by James Kim. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

Topics · follow one to build your own front page
AmazonAmazon MarketplaceAWSAmazon SageMaker AIVision-Language Models (VLMs)CatBoost classifierOptical Character Recognition (OCR) modelSHapley Additive exPlanations (SHAP)

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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