The startup develops a predictive agriculture system that provides farmers with data-driven insights to monitor greenhouse gas emissions and enhance soil carbon sequestration. This technology enables farmers to adapt to climate change impacts while generating carbon credits through improved agricultural practices.
Funding
$5.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Farmers face increasing challenges in adapting to climate change, including the need to monitor and mitigate greenhouse gas emissions and improve soil health for long-term sustainability. Traditional methods for measuring soil carbon sequestration and predicting climate-related threats are often inaccurate, costly, and lack real-time insights. This makes it difficult for growers to make informed decisions and optimize their practices for both environmental and economic benefits.
Solution
Agrology provides a predictive agriculture platform that empowers farmers with real-time, ground-truth data and machine learning-driven insights to optimize regenerative farming practices. The platform combines in-ground sensors, canopy-level monitoring, and local weather data to deliver comprehensive analytics on soil health, carbon flux, and climate threats. Agrology's system enables growers to quantify the impact of their regenerative practices, manage resources efficiently, and adapt to changing environmental conditions. By providing accurate measurements and predictive capabilities, Agrology helps farmers improve crop quality, reduce environmental impact, and enhance profitability.
Target Audience
Agrology serves farmers, growers, and agricultural researchers focused on regenerative agriculture, carbon sequestration, and climate change adaptation, as well as carbon project developers.
Features
- Continuous monitoring of soil carbon and nitrous oxide flux using the Arbiter system
- Real-time data on soil health and microbial activity
- Predictive analytics for smoke taint, drought, pest and disease outbreaks, and extreme weather events via the Sentinel system
- Multi-parameter ground-truth soil probes and canopy sensors
- Integration of local weather station data and publicly available agricultural information
- Machine learning models that track and interpret complex environmental challenges
- Mobile app and web portal for accessing real-time data, trends, alerts, and historical information
- Customizable reports and data APIs for integration with existing farm management systems