Graph embeddings are a new technology that learns the structure of connected data, revealing new ways to solve pressing problems and adding visibility to blind spots. They enable organizations to extract insight from their knowledge graphs, customer journeys, and transaction networks, providing predictive signals. Graph embeddings can distinguish normal behavior from anomalous transactions, identify duplicate users, improve product recommendations, discover new drugs, predict churn, and more. With the help of Neo4j Graph Data Science, businesses can put state-of-the-science techniques into production quickly, reliably, and at scale, empowering data scientists with less pain and extracting the full value from their data.