marketing_ops · media · workflow
5 ways Prime Video improves the viewing experience with generative AI on AWS
Prime Video's growing content library made it harder for customers to find what they wanted, while marketing assets were scattered across disparate systems with insufficient metadata, impeding content discovery, rights tracking, quality control, and monetization.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Personalized content recommendations
Amazon Bedrock powers personalized content recommendations on the Movies and TV Shows landing pages, curated based on viewer interests and viewing history.
Tools used
Amazon BedrockAmazon SageMakerAmazon Bedrock GuardrailsAWS BatchAmazon ECRAmazon ECSAWS FargateAmazon S3Amazon DynamoDBAmazon CloudWatchMedia2CloudAmazon NovaAmazon RekognitionAmazon Transcribe
Outcome
Prime Video enriched hundreds of thousands of assets and improved discoverability in its marketing archive, while generative AI on AWS now powers personalized recommendations, spoiler-free recaps, sports insights, audio accessibility, and video understanding across the platform.
Results
Volumesix languages
Grounding & classification
Source type: platform led case
38 fields verified against source quotes.
computer visioncontent generationdata extractionpersonalizationpredictive analyticssummarizationknowledge basemetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedmediacustomer satisfactionemployee productivitythroughput increaseplatform led caseback office opsmarketing opsdata sync enrichment