In 2019, software architect Joseph Gitau Kienjeku recognized an acute, life-threatening disparity across Sub-Saharan Africa: while medical imaging devices (X-rays, ultrasounds, and CT scanners) existed in public and private hospitals, there was fewer than 1 radiologist per 100,000 citizens. In remote rural counties, the ratio often worsened to 1 per 500,000.
Junior clinical officers, medical interns, and nurses were forced to make urgent diagnostic decisions on complex trauma X-rays, cavitary tuberculosis, and pediatric pneumonia without specialist oversight. Delayed interpretations meant delayed care.
Foreign commercial AI solutions were either astronomically expensive, dependent on high-speed internet connections unavailable in rural dispensaries, or exhibited systematic diagnostic bias on darker skin tones and African pathology presentations.
Our Founding Pledge: To engineer sovereign, highly optimized medical AI foundation models trained directly on diverse global and African clinical datasets, deployable on standard Android mobile hardware with micro-metered KES 5 M-Pesa billing, while guaranteeing 100% patient data sovereignty through client-side AES-256 In-App Vault encryption.
