Nexleaf Analytics' first client will be Project Surya , an unprecedented initiatve sponsored by the United Nations Environment Programme. Nexleaf Analytics will develop a mobile phone platform to profile indoor air pollution and pollution exposure on an individual scale. Nexleaf's platform will be used to scientifically and scalably document the public health and environmental impacts of introducing clean-cooking technologies to 15,000 villagers in rural India.

Project Surya aims to mitigate the regional impacts of global warming by immediately and demonstrably reducing atmospheric concentrations of black carbon, methane, and ozone. Together, black carbon (BC), methane, and ozone are responsible for 30% to 50% of the human effects on global warming. The major co-benefits of reducing these air pollutants will include immediate improvements in public health, agricultural productivity and economic development for the rural populations in developing nations.

In its first phase, Project Surya will target three regions in rural India: one region in the Himalayas, one region in the Indo-gangetic plains, and one region in South India for deployment. Surya will provide sustainable, effective, incentive-based plans to enable 5,000 households in each region to switch to cleaner-burning technologies such as solar cookers and lamps, biogas plants, and other efficient stove technologies.

Nexleaf Analytics will collect empirical evidence to quantify the climate and public health impacts of the clean-cooking intervention for Project Surya. We will pioneer the capture of continuous climate and public health data at unprecedented resolution and scale using mobile phones in concert with cloud computing. The benefit of mobile phones and cloud computing technology in this context is that, for the first time, the climate and health interventions. outcomes can be measured in real time and on a continuous basis. This results in a more complete, accurate data set, eliminating the need to rely on retrospective recall and allowing us not to miss individual, and potentially critical, climate- or health-related events that periodic or spot measurements might overlook.