MAKBeTh (AgroExact & Beyond Weather) is one of the MIT AI projects funded in 2025. MAKBeTh develops AI-driven decision support that combines hyperlocal field measurements with short- and long-term weather forecasts. The project focuses on improving decision-making in agriculture and nature conservation, enabling users to respond more quickly to conditions such as drought, precipitation, and heat.
AgroExact and Beyond Weather are combining their expertise
With MAKBeTh, two complementary partners are combining their expertise. AgroExact provides local weather and soil data to growers through a dense monitoring network, an agriculture-focused app, rain gauges, and soil moisture sensors. This gives users insight into current conditions on and around their fields. Beyond Weather brings AI, climate science, and long-term weather forecasts to the table: the company develops models that translate forecasts spanning weeks to months into actionable, interpretable insights. Together, they combine real-time field data with forward-looking weather information.
Converting weather data into actions
The core of MAKBeTh lies in translating that combined weather information into concrete courses of action. While growers and land managers currently often rely on isolated measurements, generic weather forecasts, and their own experience, MAKBeTh aims to combine this information more intelligently and apply it to specific decision-making moments. Think of recommendations regarding irrigation, crop protection, fieldwork planning, harvest times, and the early identification of drought or precipitation risks. For nature management, the same approach can help better time weather-dependent management decisions, for example regarding water availability, drought stress, or vulnerable periods in the landscape.
In this way, MAKBeTh helps users not only track weather data but also translate it into timely, evidence-based actions. This enables agricultural businesses and nature conservationists to allocate water, labor, and resources more effectively, minimize damage caused by extreme or unusual weather, and gradually make their operations more climate-resilient.
