With a focus on data relationships, Arcurve's Director of AI and ML Technology and Senior Data Scientist use Graph Data Science to combine structured and unstructured data, offering a more natural way to answer critical data science questions like prioritization, anomalies, and predictions. They leverage Neo4j Graph Data Science to break complex files into data, find patterns in the resulting structure, and create comprehensive "knowledge assets." These knowledge assets can help organizations identify similarities between legal documents, improve the accuracy of financial impact measures, and prioritize abandoned well sites for remediation based on public safety and environmental risk.