50M+ nodes, 500M+ edges, 40+ entity types powering intelligent recommendations and cultural insights
Graph traversal finds events matching user preferences, social connections, past attendance, cultural background
Impact: 3x click-through vs traditional ML
195 countries, 250+ languages, Hofstede dimensions mapped to events. Graph connects cultural attributes to event success patterns
Impact: 40% higher international conversion
Graph patterns identify suspicious behavior: fake accounts, ticket scalping, coordinated abuse
Impact: 95% fraud detection accuracy
Natural language queries traverse graph: "rock concerts near me this weekend with outdoor seating" → Multi-hop graph query
Impact: <100ms P95 latency