Trust & Security

We implement end-to-end encryption for all patient data, use federated learning techniques that keep sensitive data on local devices, and comply with international healthcare data protection standards. We never sell patient data and only use anonymized data for improving our AI models with explicit consent.

Our diagnostic tools have been validated through rigorous clinical trials, achieving accuracy rates comparable to human specialists in many cases. However, we always emphasize that our tools are designed to assist healthcare professionals, not replace them. We provide transparency about confidence levels and limitations for all AI-generated insights.

Our AI models are trained on diverse datasets from across Africa, incorporating cultural nuances in how health and illness are understood and described. We work with local healthcare providers and community representatives to ensure our solutions are culturally appropriate and respectful of local beliefs and practices.

Our solutions are designed to work in low-connectivity environments. Many features can function offline, with data syncing when connectivity is available. We also optimize our applications to work with minimal bandwidth and on basic smartphone devices.

We actively work to identify and mitigate biases in our AI systems through diverse training data, regular bias audits, and ongoing monitoring. Our team includes experts in AI ethics who review our systems for potential biases, and we're transparent about the limitations of our technology.

We implement multiple layers of security, including end-to-end encryption, secure authentication, regular security audits, and compliance with international security standards. Our systems are designed with a 'security by design' approach, and we conduct regular penetration testing to identify and address potential vulnerabilities.