Agriculture

From seed-level field data to global supply chains, agriculture is full of interacting causes that population averages hide. Causal AI separates what actually drives yield and risk from what merely correlates with it.

Precision crop optimization: causal AI from planting to harvest

John Deere Startup Collaborator Program

Challenge

Modern precision equipment generates rich planting, field and environmental data, but more data does not automatically improve yield. Conventional analytics could not distinguish which controllable factors were genuinely causing yield variation from those that were simply correlated with it.

Approach

Working on a John Deere test farm with individual seeds geo-tagged at planting, Geminos built causal models across seven crop growth stages for soybean and corn, with early-stage outcomes feeding into later-stage analysis to reflect how crop performance accumulates across the season.

Outcome

The project produced a repeatable framework for identifying the specific controllable drivers of yield variation at each growth stage. Planting prescriptions, fertilizer timing, irrigation and harvest timing could all be improved based on causal evidence, with the framework transferable to commercial farming.

Causal AIML/DLKnowledge Graph

Eliminating deforestation from the palm oil supply chain

Global consumer goods company

Challenge

A major consumer goods company faced NGO accountability and declining consumer trust due to deforestation linkages in its palm oil supply chain. Existing geo-spatial monitoring only detected deforestation after it had occurred.

Approach

Causal models for deforestation risk, audit outcomes and brand impact were built using internal supplier data and external sources including global tree cover data, palm oil trade flows and socio-economic indicators. An Enterprise Knowledge Graph mapped the supply chain network with certification status and risk attributes.

Outcome

Each supplier received a quantified risk profile, enabling proactive replacement or escalation of high-risk relationships before incidents occurred. Audit resources were redirected to the highest-risk suppliers, and the platform provided an evidence-based foundation for sustainability reporting.

Causal AIKnowledge GraphLLMML/DL

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