Neo4j has released a new version of its Graph Data Science Platform, making it easy for data scientists to start using Google Cloud with Neo4j AuraDS, a fully managed graph data science offering. This platform allows users to amplify their machine learning pipelines by feeding knowledge of the graph into ML models to enhance predictability. Graphs are becoming increasingly important in various industries, such as pharmaceuticals and finance, where they help analyze relationships between people, places, objects, and events. Neo4j AuraDS provides access to over 65 state-of-the-art graph and machine learning algorithms, along with a simple hourly pricing model, making it easy for users to understand and manage costs associated with compute. The platform is designed to be user-friendly, allowing users to create instances with minimal configuration, resize them as needed, and pause them when not in use. AuraDS can be integrated with Vertex AI, providing a seamless workflow for machine learning pipeline development and deployment. The integration allows users to generate graph embeddings using FastRP, train models on them, and deploy the trained model for new predictions. With Neo4j Graph Data Science, data scientists can focus on building their business while leveraging a complete platform that makes it easy to start and take their use case from hypothesis to production without requiring a team of software engineers or database managers.