Chronic shortage of doctors in rural India seriously impacts the quality of healthcare available to villagers. In recent years, there has been considerable excitement in digital diagnostics as a possible answer to this situation by allowing non-doctors to diagnose and treat patients. This paper focuses on one such diagnostic tool that has gained serious traction amongst transnational health foundations and state governments alike. Here the focus is on the customization and localization of this software through a pilot study in Central Himalayas. A baseline survey and extensive interviews are conducted for categorization and population of health data content. This entailed analyzing the segmentation and transfer of health information on disease history and symptoms from the patient to the software as well as situating this study in the larger understanding of the healthcare system in this community. In doing so, this paper argues that much of such health information is difficult to categorize and sufficiently vague to provide for confident diagnostics. Further, the data population of the treatment segment is deeply political and socio-cultural. Thereby this paper problematizes the innate assumption underlying the design of such software that it is possible to diagnose and treat patients based on pure information.