Zivia Ag
Stop Guessing, Start Growing
Make smart agricultural decisions that balance profitability with environmental stewardship. Our integrated physically-based and AI-driven modeling tools take the guesswork out of crop management and conservation practices, giving you precise, scientifically-validated insights into crop yield, soil health, water consumption and quality, and greenhouse gas emissions.
Sustainability teams must optimize management aspects such as water use, soil health, nutrients, and production technology to achieve profitable Ag production outcomes.
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Traditional approaches fail to provide the defensible modeling required for modern reporting. Zivia Ag bridges this gap:
Scientific Rigor
Unlike home-grown tools, we use globally-recognized mechanistic models that are scientifically validated.
Enterprise-Grade Visualization
We transform complex data into configurable, easy-to-interpret visuals for high-level reporting.
Eliminate Trade-off Complexity
Easily compare multi-faceted options to ensure every dollar invested delivers the maximum environmental impact.
Scalable SaaS Model
Encode organizational knowledge into software that grows while reducing long-term development costs.
Our Best-In-Class Module Library
We use globally-recognized models to create tailor-made solutions.
Cropland Soil Carbon
Advanced carbon budget simulations using the SWAT+ model, featuring site-specific calibration and uncertainty quantification.
Water Quality & Erosion
Accurate field-to-watershed scale estimates of soil erosion and pollutants (N and P).
GHG Calculator
Comprehensive greenhouse gas budgets.
Irrigation Scheduling
Real-time sensor and remote-sensing data assimilation for precision variable-rate irrigation.
Soil & Water Conservation
Machine learning-driven insights into water quality and the effects of agricultural conservation practices.
Nutrient Recommendations
Agronomic N and P fertilizer rates based on physiographic and climatic conditions.
Our Best-In-Class Module Library
We use globally recognized models to create tailor-made solutions.
Advanced carbon budget simulations using the SWAT+ model, featuring site-specific calibration and uncertainty quantification.
Cropland Soil Carbon
Real-time sensor and remote-sensing data assimilation for precision variable-rate irrigation.
Irrigation Scheduler
Comprehensive greenhouse gas budgets powered by SWAT+ and Daycent models.
GHG Calculator
Real-time sensor and remote-sensing data assimilation for precision variable-rate irrigation.
Rangeland Hydrology
Machine learning-driven insights into water quality and the effects of agricultural conservation practices.
Soil & Water Conservation
Specialized simulations for rangeland systems using the REM model.
Rangeland Hydrology
Accurate field-to-watershed scale estimates of soil erosion and pollutants (N and P).
Water Quality & Erosion
Agronomic N and P fertilizer rates based on physiographic and climatic conditions.
Nutrients
We Build The Full Stack
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Custom Applications: Tailored interfaces designed specifically for the unique workflows of water and Ag analysts.
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Platform Configuration: A modular, service-oriented architecture allows for rapid microservice deployment and AI/ML integration.
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Cloud Management: Flexible, scalable deployment options across AWS, Microsoft Azure, or on-premises servers.
Our Story
Born at Colorado State University
For over 20 years, our team has pioneered the use of biogeochemical models powered by AI to advance environmental sustainability. We are dedicated to solving real-world problems for landowners, government agencies, and municipalities through world-class research.
Field to Market utilizes Zivia Ag to process and quantify sustainability metrics through various models, providing data-driven insights to their network of members.
