Our team brings together the key technical and design skills required to build a complete AI-assisted diagnostic platform, from hardware to cloud.
Our team lead is a medical student and also the backend engineer building the core infrastructure — APIs, databases, authentication, and communication systems that connect the AI engine, user interfaces, and hardware. Our frontend engineer is developing both the web and mobile interfaces for viewing slides, triggering diagnoses, generating reports, and enabling real-time collaboration. Our AI engineer, a student of the computer science, is focused on model training and deployment, building deep learning pipelines using computer vision, CNNs, and inference optimisation for edge devices. Our product designer is crafting intuitive, user-centred interfaces and diagnostic flows, ensuring clarity and usability in high-stakes clinical settings. Our embedded systems engineer is developing the hardware prototype — including optics, camera integration, slide loading, edge computing, and power systems — all designed to work reliably in low-resource environments.