SecretFlow provides an abstract device layer that encapsulates cryptographic protocols and a device flow layer that models algorithms as directed acyclic graphs. Its algorithm layer supports data analysis and machine learning with horizontally or vertically partitioned data, while the workflow layer integrates data processing, model training, and hyperparameter tuning. The framework combines federated learning, homomorphic encryption, secure multiparty computation, and trusted execution environments to enable collaborative ML without exposing raw data.