Graph-Powered Compliance: Building Intelligent Regulatory Mapping with AI and Neo4j

Session Track: Knowledge Graphs & GraphRAG

Session Time: 09:30 am - 10:00 am April 15

Session description

Cloud computing has transformed enterprise operations, yet traditional compliance approaches relying on annual audits and manual documentation fail to address the dynamic nature of modern environments where resources can exist for mere minutes. This presentation explores how graph databases combined with artificial intelligence create intelligent compliance ecosystems that transform regulatory requirements from reactive liabilities to strategic enablers.

Traditional compliance models impose significant operational burdens with lengthy audit preparation cycles and resource-intensive manual processes. Graph-based compliance architectures fundamentally change this paradigm by modeling relationships between controls, regulations, assets, and evidence as connected networks rather than isolated data points. Neo4j’s native graph capabilities enable organizations to traverse complex regulatory hierarchies, identify control gaps through relationship analysis, and visualize compliance dependencies across multi-cloud environments.

The technical foundation leverages compliance-as-code methodologies encoded within graph structures, enabling control validation requirements to be automatically triggered within CI/CD pipelines. Machine learning algorithms traverse regulatory knowledge graphs to extract requirements from documentation, while graph-based anomaly detection identifies potential control failures through pattern recognition across connected compliance networks. The Open Security Controls Assessment Language (OSCAL) integrates seamlessly with graph architectures, providing standardized formats that enable interoperability across diverse compliance frameworks.

This session addresses critical implementation considerations including graph schema design for regulatory mapping, integration strategies for hybrid and multi-cloud environments, and approaches to managing alert fatigue through graph-based risk prioritization. Attendees will learn how organizations leverage Neo4j’s relationship modeling to achieve continuous control validation across heterogeneous infrastructure while maintaining real-time visibility into compliance posture.

As regulatory complexity intensifies across AI governance, data sovereignty, and emerging frameworks, graph-powered compliance represents the essential evolution enabling organizations to innovate confidently while maintaining continuous regulatory alignment.