This system analyzes Canada's development programming in agriculture and food to understand how well projects align with high-impact interventions from the Ceres2030 framework, which supports the United Nations Sustainable Development Goal 2 (zero hunger). Using machine learning and natural language processing, the system automatically extracts project characteristics and outcomes from departmental reports to identify causal relationships and support portfolio analysis.
The system processes unstructured project documents and reports to create structured data that enhances existing departmental reporting capabilities. This analysis helps inform whether development interventions and approaches—individually and jointly—meet strategic, programmatic, and policy needs related to sustainable agriculture and food security.
Note: This system is now retired. It does not process personal information and was primarily used by Government of Canada employees. The system was developed by the University of Notre Dame as a vendor partner.
