With tools for building applications and deploying and managing federated learning workflows, FLARE lets researchers and data scientists adapt their machine learning and deep learning workflows to a federated paradigm. Together, we’ll explore the architecture, key concepts, components, and capabilities of the platform. We’ll also check out the built-in algorithms for federated training and evaluation with privacy preservation and highlight the tools that help developers come up to speed quickly. Finally, we’ll take a look at what it takes to go from a proof-of-concept simulation to real-world deployment.