Using Strands Agents to create a multi-agent solution with Meta’s Llama 4 and Amazon Bedrock

This article demonstrates building a multi-agent video processing workflow using Strands Agents, Meta's Llama 4, and Amazon Bedrock for automated video analysis through specialized AI agents.

• Multi-agent systems provide scalability, resilience, specialization, and dynamic problem-solving for complex enterprise tasks
• Meta's Llama 4 Scout supports 10M token context; Llama 4 Maverick supports 1M tokens for multimodal processing
• Solution uses six specialized agents: coordinator, frame extraction, visual analysis, JSON retrieval, temporal analysis, and summary generation
• Agents as Tools pattern wraps specialized agents as callable functions for seamless inter-agent communication
• Video workflow: extract frames → analyze visually → retrieve JSON → temporal reasoning → generate summary
• Deployable via Jupyter Notebook or Gradio UI with Amazon S3 for storage and Amazon Bedrock for inference
• Extensible architecture supports smart cities, industrial automation, surveillance, and media management use cases

This approach enables modular, maintainable multi-agent AI solutions that leverage AWS infrastructure for scalable video understanding and analysis.