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The chronic shortage of doctors in rural India seriously impacts the quality of health care 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. In this article, the author focuses on one such diagnostic tool that has gained serious traction among transnational health foundations and state governments alike. 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, the author argues that much of such health information is difficult to categorize and sufficiently vague to not provide for a confident diagnosis. Further, the data population of the treatment segment is deeply political and sociocultural. This article thereby problematizes the innate assumption underlying the design of such software, that it is possible to diagnose and treat patients based on pure information. [ABSTRACT FROM AUTHOR]