Project Description:

Maternal mortality rates in Sub-Saharan Africa continue to face the highest burden, accounting for over 70% of global maternal deaths — most of which are preventable. In many low- and middle- income countries (LMICs), labor is managed by skilled birth attendants (SBAs), who are responsible for monitoring progress and supporting delivery. However, in many facilities, the number of births far exceeds the number of SBAs. SBAs are under extreme pressure, leading to overwork and reduced attention per patient.

Labor care requires rapid and accurate clinical decisions based on evolving factors like fetal heart rate, cervical dilation, and maternal vitals. Yet current support systems fail to accommodate the dynamic nature of labor. As a result, SBAs are left without timely, intelligent tools to assist them, causing missed complications and delayed interventions
Kujali is an AI-powered mobile application that integrates seamlessly into the clinical workflow, offering real-time, context-aware, patient-specific support to birth attendants.

Project Photo:

In rural maternity clinics, skilled birth attendants are often overwhelmed by the number of patients they must care for. This project highlights the urgent need for intelligent, real-time decision-support tools to enhance maternal care, reduce complications, and support overburdened healthcare workers during labor and delivery in low-resource settings.