A recap of an Arango community meetup exploring why graph-native connected data improves AI accuracy in agentic workflows. The session covered the Arango Contextual Data Platform's three-layer architecture: unified ingestion via AutoGraph (with automatic entity resolution and community detection), adaptive retrieval via AutoRAG (blending graph traversal and vector search at runtime), and built-in governance with full lineage. A live demo showcased Contextus, a custom graph-guided discovery agent built on Arango 4.0 using LangGraph ReAct, GraphSAGE embeddings, and multi-hop traversal to surface non-obvious 'dark edge' relationships in a 30-year semiconductor design dataset. Key points include graph traversal cost scaling with edges walked rather than collection size, model-agnostic support, and air-gapped deployment compatibility.
