Description: Ubenwa, founded in 2019 by Charles Onu in Lagos, Nigeria, is a health-tech startup using AI to combat neonatal mortality. Its flagship tool employs signal processing and deep learning to analyze infant cries, detecting birth asphyxia—a condition affecting 1.2 million newborns annually in Africa—with 90% sensitivity. The system processes audio features like pitch and frequency, requiring only a smartphone and no internet, ideal for Nigeria’s rural clinics where 60% lack diagnostic equipment. Piloted in 10 hospitals in Lagos and Abuja, Ubenwa screened 2,500 newborns by 2024, identifying 300 cases for urgent care. The startup collaborates with the Nigerian Medical Association and UNICEF to validate its algorithms and train nurses. Funded by $2 million from Google for Startups and the Bill & Melinda Gates Foundation, Ubenwa is refining its dataset with African-specific cry patterns to reduce bias from Western-centric models. Plans include scaling to 50 hospitals in Nigeria by 2026 and entering Kenya and Uganda, alongside developing AI for other neonatal conditions like sepsis.
Impact: Ubenwa’s screenings have saved approximately 200 infants by enabling interventions within the critical first hour of life. Costing less than $1 per test, it addresses Nigeria’s neonatal mortality rate (34 per 1,000 births), saving hospitals $500,000 annually in diagnostic costs.
Challenges: Non-African training data risks algorithmic bias, necessitating local data collection. Regulatory approval from Nigeria’s NAFDAC is pending, delaying nationwide adoption. Low smartphone literacy among rural health workers requires extensive training.
