Automate video analysis workflows using AI-powered agents to assess content moderation flags, regional ratings, and rights validation in a fraction of the time required by manual review. Reduce the operational burden on compliance teams while increasing the consistency and accuracy of content decisions.
Overview
This Guidance demonstrates how to accelerate content compliance review by using Amazon Bedrock and Amazon Nova to analyze video and image content across multiple rating systems. It automates moderation of long-form content, including multi-hour feature films, producing frame-level and timestamp-level detail that helps reviewers pinpoint flagged moments. Amazon Bedrock Agents enrich results by validating content rights, performing quality control, and incorporating external metadata. By reducing review times from hours to minutes and lowering costs, it delivers consistent results across large content libraries and helps compliance officers focus on decisions that require human judgment across complex, multi-regional requirements.
Benefits
Accelerate content compliance reviews
Scale reviews without added overhead
Use serverless orchestration and foundation models to process video assets at scale, eliminating the need to provision or manage additional infrastructure as your content library grows. Your teams can focus on editorial decisions while automated workflows handle transcription, frame-level analysis, and metadata enrichment.
Strengthen compliance with enriched metadata
Leverage AI agents grounded in indexed compliance standards and external data sources to validate content rights, perform quality control checks, and augment moderation with third-party metadata. This multi-layered approach helps your organization apply consistent, auditable compliance standards across all media assets.
How it works
This architecture diagram illustrates how to build and operate Automated Content Compliance with AI-powered Video Analysis and Agents on AWS. It shows the key components and their interactions.
Download the architecture diagram
Step 1
Moderators authenticate to the web UI, served by an Amazon CloudFront distribution with protection provided by AWS WAF. Amazon Cognito provides user authentication.
Upload raw video (and optional transcript) for compliance analysis to Amazon Simple Storage Service (Amazon S3).
A workflow to generate metadata required for the compliance analysis is triggered by an AWS Lambda function.
AWS Step Functions state machines coordinate the ingestion and analysis workflows.
The ingestion analysis workflow generates playback assets and frames from the video. If a transcript is not included it is generated using Amazon Transcribe.
Amazon Nova generates contextual analysis of the full video and detects Regional Ratings as well as Content Moderation Flags.
Based on the results of the full video level analysis, an AWS Lambda function is triggered to generate a more detailed frame-level report. A configurable foundation model in Amazon Bedrock uses visual understanding to generate a timeline report of moderation flags.
Amazon Bedrock Agents leverage standards and external metadata indexed with Amazon Bedrock Knowledge Bases to validate content rights, review metadata for quality control, and augment the content moderation with IMDb data.
Amazon S3 stores the media files and reports, while Amazon DynamoDB tables store analysis results and statistics generated during the workflow.
Analysis results are surfaced in the timeline view of Fonn Group's Mimir.
Deploy with confidence
Everything you need to launch this Guidance in your account is right here.
Let's make it happen
Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs.