Knowledge Graph: Entity & Relationship Explorer
A Neo4j-powered knowledge graph with 31 OWL entity types maps every regulation, obligation, risk, and control. Session graphs merge into workspace-level intelligence that compounds over time.
How the Knowledge Graph Builds
From extracted entities to visual exploration
Entities Extracted
Every AI interaction generates structured entities using 31 OWL entity types: regulations, obligations, rights, risks, and more.
Relationships Mapped
Entities are connected through typed relationships: requires, conflicts-with, supersedes, applies-to -- building a living regulatory map.
Graph Grows
Session-level knowledge graphs merge into workspace-level graphs. Cross-session insights compound over time.
Visual Explorer
Navigate the graph interactively. Click any entity to see its connections, evidence sources, and regulatory context.
Knowledge Graph Capabilities
Map, explore, and reason over regulatory relationships
31 OWL Entity Types
A purpose-built ontology for AI governance: regulation, article, obligation, right, risk, control, evidence, and 24 more entity types.
Session Knowledge Graph
Each chat session builds its own knowledge graph. Entities and relationships are extracted in real time as you interact.
Workspace Knowledge Graph
Session graphs merge into a persistent workspace-level graph. Cross-session insights accumulate and compound.
Visual Explorer
Interactive Neo4j-powered graph visualization. Pan, zoom, filter by entity type, and click nodes to explore connections.
Cross-Framework Links
See how entities from different frameworks relate. A GDPR article linked to an EU AI Act obligation reveals compliance overlaps.
Export & API
Export graph data as JSON-LD or access via REST API. Integrate knowledge graph insights into your compliance systems.
136days until enforcement
Explore Your Regulatory Graph
Start building your knowledge graph with every AI interaction. Free plan included.