Expert agronomic prediction, crop modeling with APSIM & DSSAT, soil carbon analytics, remote sensing, and AI integration — for researchers, NGOs, and agribusinesses worldwide.
Farmers lose yield. Researchers waste time. NGOs miss impact. Not from lack of effort — but from lack of the right tools and expertise to turn data into confident decisions.
Without calibrated crop models, management decisions are based on rules of thumb that miss critical interactions between soil, climate, and variety.
Organizations collect satellite and drone imagery but lack the agronomy expertise to convert it into yield maps, management zones, or actionable recommendations.
Grant proposals, field trials, and development programs need APSIM/DSSAT expertise and experimental design — but specialist support is hard to find and expensive.
Each pillar is a complete, standalone service — or combine them for integrated farm-to-policy decision support.
Mechanistic crop modeling and AI-enhanced prediction for yield forecasting, risk estimation, and climate-smart management — calibrated to your specific crops and conditions.
Converting drone and satellite imagery into decision-ready outputs — yield maps, management zones, soil carbon baselines, and agronomic prescriptions backed by crop science.
Supporting research projects, grant proposals, and agricultural development programs — with training, experimental design, and digital tool development for researchers and NGOs.
We are not agronomists who learned to code, or data scientists who read about farming. We are both — with boots-on-ground experience across four continents and deep technical expertise in crop simulation and AI.
Every deliverable is grounded in peer-reviewed crop science and validated model outputs — not generic AI or desktop analysis without field calibration.
Smallholder systems in Ethiopia, precision agriculture in Japan, broadacre modelling in Australia, and carbon markets in the USA — context matters, and we have it.
We go beyond traditional crop modeling — connecting APSIM and DSSAT outputs with machine learning, remote sensing, and conversational AI tools for decision support.
Our methodologies meet peer-review and regulatory standards — suitable for journal submission, grant reporting, and carbon credit verification.
Completed engagements demonstrating our methodology across continents and client types.
A midwest grain cooperative needed scientific validation of legume-derived nitrogen credits to enter a voluntary carbon market. Generic lookup tables created compliance risk and underestimated true fixation.
An international NGO needed evidence-based recommendations for integrating legumes into smallholder mixed cropping systems in the Ethiopian highlands to improve soil nitrogen and food security.
Hands-on training in APSIM, DSSAT, remote sensing, and AI integration — for researchers, postgraduates, NGO staff, and agricultural development programs.
Enquire About Training →Calibration, scenario analysis, and output interpretation for legume-based rotations.
Model setup, genetic parameter estimation, and climate scenario analysis across 45 crops.
Converting drone and satellite imagery to yield maps, management zones, and NDVI analytics.
Connecting APSIM/DSSAT with Python ML pipelines, GPT APIs, and decision support tools.
Every engagement is scoped to your specific problem. These are starting points, not ceilings.
Rapid crop model analysis or remote sensing assessment for a defined, specific problem.
Complete crop modeling + remote sensing analysis with AI integration and carbon advisory.
Ongoing monthly modeling support for research programs, NGOs, and agtech companies.
Whether you need a rapid crop diagnostic, a full modeling study, or training for your team — start with a free 30-minute discovery call. No obligation, no pressure.