The field as a continuous, sensed system.

Autonomous tractors + implements

John Deere 8R-class autonomous tractors use 6 stereo-camera pairs + neural-network navigation and scan soil quality during operation. Case IH, AGCO, Kubota all ship autonomy SKUs. The platform brokers across vendors: a single farm running mixed iron gets one operations layer, not three. Field plans, service windows, and shift handoffs are coordinated centrally; the cabs run themselves.

Precision herbicide + nutrient (See & Spray pattern)

Blue River / John Deere See & Spray distinguishes weeds from crops with vision and sprays only where needed — documented 59% average herbicide reduction across corn, soybean, and cotton; over 1M acres treated in 2024. The platform extends the same pattern to nutrients, pesticides, and growth regulators across non-Deere implements through a vendor-agnostic agent.

Drone scouting + thermal mapping

Single thermal-camera drone flights survey vineyards in under an hour, detecting irrigation breaks and stressed canopy from sub-degree thermal differences. The platform fuses drone imagery with satellite NDVI and field weather to produce per-block decision support — variable-rate prescriptions, irrigation activations, scout-team routing.

Irrigation MPC + water savings

Soil moisture + ET₀ + weather forecast drive zone-specific irrigation schedules with documented 30% water savings. The platform runs MPC controllers per irrigation block, integrates with pivot and drip controllers, and respects regulatory water-rights constraints automatically.

Livestock & dairy AI

AI in precision livestock farming is a $3.45B market in 2026, projected to $8.01B by 2030 (27.9% CAGR). Computer vision identifies individual animals, scores body condition, detects lameness, predicts calving time. Wearables + RFID + accelerometers track activity, location, and health. The platform shifts management from herd-level to individual-animal — the welfare and economic case both improve.

Greenhouse + indoor / vertical farming

CO₂, humidity, light, nutrient delivery, harvest timing — closed-environment agriculture is a process-industry problem with visual + biological signals layered on. The platform runs the full process-control stack (RL on dosing loops, vision for harvest readiness, predictive maintenance on HVAC + pumps) on top of the existing greenhouse-management system.