Medical Legal Regulatory Review Orchestration with AI Agents on AWS

This article describes a multi-agent AI system built on Amazon Bedrock that accelerates medical, legal, and regulatory (MLR) content review for healthcare companies.

• MLR review currently takes ~15 days per document with manual cross-functional teams examining content line-by-line
• AI agents can reduce review time by up to 90% while maintaining regulatory compliance and patient safety standards
• System uses specialized parallel agents for scientific accuracy, regulatory compliance, branding, and pre-approved claims verification
• Six-step workflow: document processing, content batching, statement extraction, claims verification, expert review, result compilation
• Achieves over 70% recall in proof-of-concept testing; processes multi-page documents in ~2 minutes per batch
• Built on Amazon Bedrock AgentCore, Strands Agents SDK, and includes RAG with Knowledge Bases for dynamic reference materials
• Web UI allows users to upload content and launch reviews with single click; outputs structured JSON reports with flagged issues and suggested fixes

The solution demonstrates how decomposing MLR review into specialized AI agents can accelerate pharmaceutical content approval while preserving human expert oversight for final decisions.