A graph represents relationships between entities such as people, devices, locations, etc. Graph AI applies neural/convolutional network techniques on graphs to provide insights when the relationships between entities is as important as the entities’ attributes themselves.
Interpret many-to-many relationships in unstructured, fluctuating, variable datasets to enhance the accuracy of predictions
Enhance classification, pattern detection, and prediction accuracy when combined with AI-ML Graph Neural or Convolutional Networks (GNN/GCN)
Support visualizations to express large and complex interconnected data and help you discover relations between entities