Organisation Name
Paybuddy
Industry
Health services
Organisation Website
Country
Nigeria
Sustainable Development Goals (SDGs)
SDG 3: Good Health and Well-being
SDG 9: Industry, Innovation and Infrastructure
SDG 10: Reduced Inequality
General Description of the AI tool
Ukubona is an AI-powered DICOM Viewer that supports radiologists by automatically detecting and highlighting abnormalities in X-rays. It identifies 14+ disease conditions, flags artifacts, classifies normal scans, and generates preliminary diagnostic reports in seconds. Integrated with transcription tools, it accelerates diagnosis, reduces errors, and optimizes hospital workflows in low-resource environments.
Relevant Research and Publications
WHO (2023) — “Radiology Workforce in Africa: Bridging Diagnostic Gaps.”
Ukubona Internal Pilot Report (2024) — AI-assisted X-ray interpretation at FMC Lagos.
Nigerian AI Research Scheme (2024) — Localization of healthcare AI datasets.
World Bank (2023) — “AI Adoption in Emerging Market Health Systems.”
Radiology Society of Nigeria (2024) — “Digital Radiology in Resource-Limited Hospitals.”
Needs
Funding
Customers
R&D expertise
HPC resources and/or Cloud Computing Services