Postpartum depression is a serious challenge for maternal health, affecting mothers’ well-being, infant development and family stability. Although wearable devices and mobile sensing technologies can continuously collect physiological and behavioural data, most existing maternal health applications are limited to specific device ecosystems. This paper presents MAMAI (Maternal Assistance and Monitoring through Artificial Intelligence), an interoperable framework designed to support postpartum well-being monitoring by ingesting data from multiple wearable devices. The proposed system enables interoperability across different sensing platforms and healthcare infrastructures by integrating two standards: the Open Geospatial Consortium (OGC) SensorThings Application Programming Interface (API), which manages Internet-of-Things (IoT) sensor observations, and the Fast Healthcare Interoperability Resources (FHIR), which represents well-being indicators in clinically compatible formats. The system follows a three-layer edge–cloud architecture that performs local preprocessing of wearable signals, standardized data transformation, and cloud-based well-being analytics. One of the main outputs of the well-being analytics module is the composite well-being score. This score is calculated from normalized indicators derived from sleep patterns, physical activity, and heart-rate signals. By connecting consumer wearable devices with standardized healthcare data infrastructures, the proposed framework provides a scalable foundation for maternal digital health systems.