Archaeological research today struggles with siloed LiDAR data, satellite imagery, and scattered historical records. Archaios demonstrates how a cloud-native, AI-powered knowledge graph can unify these sources and enable discovery at scale.

Built on Neo4j and Azure Cosmos DB, Archaios constructs a semantic layer that links terrain models, spectral imagery, and historical documents into an interconnected knowledge graph. This foundation powers multi-agent reasoning with Microsoft’s Semantic Kernel, where AI experts — Archaeology Analyst, Terrain Specialist, and Environmental Expert — collaborate across graph relationships to surface hidden patterns, anomalies, and candidate sites.

In this session, Divakar Kumar shows how event-driven Azure Durable Functions orchestrate LiDAR and spectral processing pipelines, while graph-based representations unlock semantic search, historical context retrieval, and explainable insights. You’ll also see how gamified collaboration enables archaeologists and explorers to contribute knowledge back into the graph, creating a living, evolving map of human history.

Whether you’re building intelligent applications, scaling knowledge-centric systems, or exploring how Neo4j + multi-agent AI can transform real-world domains, this session will inspire you to think beyond data pipelines and into knowledge-driven discovery.