Cloud Compliance Agent for EU DMA
Develop a cutting-edge multi-agent system designed to automatically analyze cloud service providers' (AWS, Azure, Google Cloud) compliance with the EU's Digital Markets Act (DMA) and assess the impact of major outages. This challenge emphasizes building a robust, graph-based workflow using LangGraph to orchestrate agents specialized in legal interpretation, technical risk assessment, and report generation. The system will integrate securely with simulated enterprise data and regulatory documents via the MCP, demonstrating advanced reasoning and adaptive thinking capabilities to provide actionable compliance insights.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a graph-based multi-agent system using LangGraph with Claude Opus 4.1 for automated EU DMA compliance analysis and cloud service risk assessment, leveraging the Model Context Protocol.
How work is evaluated
The evaluation will assess the LangGraph agent system's ability to accurately identify compliance issues, assess outage risks, and generate coherent, actionable reports, emphasizing secure Model Context Protocol integration and adaptive reasoning.
Challenge datasets
Public datasets, plus the private datasets you have access to.
What you should walk away with
Utilize Claude Opus 4.1 for sophisticated legal text interpretation and risk assessment.
Design and implement a graph-based multi-agent workflow for regulatory compliance using LangGraph.
Implement adaptive thinking budgets for agents to dynamically allocate reasoning resources based on task complexity.
Generate comprehensive compliance reports and risk mitigation strategies.
Integrate Model Context Protocol (Model Context Protocol) for secure access to enterprise data and external regulatory documents.
Reference links and supporting material
Sample data for 1 tasks
Challenge setup
The evaluation will assess the LangGraph agent system's ability to accurately identify compliance issues, assess outage risks, and generate coherent, actionable reports, emphasizing secure Model Context Protocol integ...
Challenge input
{'outage_report': 'text', 'cloud_usage_data': {'service_id': 'str', 'data_location': 'str', 'interoperability_features': 'bool'}, 'dma_articles': [...
Agent execution
No agent tool is listed for this challenge.
Evaluated output
{'compliance_issues': [{'article': 'str', 'description': 'str', 'severity': 'str'}], 'outage_risk_assessment': {'impact': 'str', 'mitigation_sugges...
- The system identifies at least one critical DMA compliance issue related to the input scenario.
- The system provides at least two relevant mitigation suggestions for the outage risk.
- ComplianceIssueAccuracy target: 0.85
- Python execution harness
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
No tool records are attached.
Evaluation contract
- The system identifies at least one critical DMA compliance issue related to the input scenario.
- The system provides at least two relevant mitigation suggestions for the outage risk.
Metrics
- ComplianceIssueAccuracy · Target 0.85
- ReportCompleteness · Target 0.9
Workflow tasks
- Task 1
Input: {'outage_report': 'text', 'cloud_usage_data': {'service_id': 'str', 'data_location': 'str', 'interoperability_features': 'bool'}, 'dma_articles': ['text']}
Output: {'compliance_issues': [{'article': 'str', 'description': 'str', 'severity': 'str'}], 'outage_risk_assessment': {'impact': 'str', 'mitigation_suggestions': ['str']}, 'reasoning_path': 'graph_representation'}
Execution harness: Python
Recipe freeze marker
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