Yield and inputs
Variable-rate application and field-level forecasting that reduce input cost per tonne.
Industry
Farms, processors, and food supply — thin margins, volatile inputs, growing demand.

Agriculture operates on biological timescales with financial margins that leave little room for error. Input costs, weather, and yield variability dominate the result.
The data now exists to manage that variability: field-level imagery, machinery telemetry, weather, and soil sensing. Turning it into decisions requires models that respect the agronomy, and interfaces that a farmer will actually use during a working day.
We work on yield, input efficiency, processing, and food supply chains, with an emphasis on adoption rather than novelty.
Illustrative client outcomes, representative of engagements in this sector.
Talk to this practiceVariable-rate application and field-level forecasting that reduce input cost per tonne.
Quality and throughput models for mills, dairies, and packing operations.
Supply-chain provenance systems that satisfy regulatory and retail requirements without adding paperwork.
Measurement of emissions, water, and soil outcomes in a form that buyers and regulators accept.
Evidence

Article
You do not need a perfect data estate. You need the twenty data products that carry your decisions to be trustworthy, owned, and fast.
4 September 2026 · 8 min read

Case study
A specialty chemicals producer lifted first-pass yield by 4.6 points by treating every batch as a training example — with operators in the loop, not out of it.
15 May 2026 · 8 min read

Next step
A ninety-minute working session is usually enough to agree the baseline, the owner, and the first evidence gate.