ListenField strives to introduce novel methods, and integrate existing technological tools, formulating them into a predictive modeling platform that will be useful for many agricultural applications. Working primarily with governments and research institutions, ListenField collects and analyzes agricultural data such as crop performance, climate resilience, and soil change, feeding their analysis back to research and government agencies to stimulate more sustainable agricultural policies. Using sensors, satellites, and self-collected data, ListenField's predictive analytic model enables both farmers and corporate clients to fully understand how these variables interact with one another for a specific crop. More precisely, they aim to develop the capability to monitor and assess how key variables individually and collectively make plants grow, produce and reproduce -- and do so remotely from anywhere in the world. The solutions derived from their models are aimed at achieving their goal of “Precision Agriculture”: to produce an abundance of high-quality crops in a way that saves on scarce resources, thereby minimizing costs as well as unwanted impacts on the environment.