A federated-learning-ready architecture is sufficient for Phase I; live federated model training is not expected until Phase II. In Phase I, the primary objective is to demonstrate the technical feasibility of the proposed predictive AI architecture and build a preliminary model or proof-of-concept for a selected freight corridor. To meet these requirements, proposals should include a high-level conceptual architecture that outlines your predictive modeling and data integration strategy. The application of federated learning methods is seen as a key technical parameter to enhance model accuracy across multiple jurisdictions while preserving data privacy. Utilizing federated data exchange protocols and APIs is also viewed as a risk mitigation strategy for handling sensitive, proprietary business information without requiring the transfer of raw data.