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Case 14/Agricultural AI/Agritech

Farmhand — Process Data Intelligence

Real-time efficiency scoring and recommendations across 50+ telemetry signals on farm equipment.

ClientJohn Deere
The challenge

What was breaking

Field operators had no real-time visibility into operations, no optimisation logic for planting and seeding density, and multi-season patterns were invisible.

The solution

Farmhand

Farmhand combines real-time efficiency scoring, recommendation engines, yield prediction and anomaly detection across telemetry, yield, soil and weather data.

  • Real-time edge plus cloud analytics
  • Efficiency scoring and variance flagging
  • Cost-weighted recommendation engine
  • Yield prediction and anomaly detection
  • Operator dashboards with daily efficiency alerts
Solution design

How it works

5 stages
  1. 01

    Sense

    50+ telemetry signals collected from tractor ECUs alongside yield, soil and weather data.

  2. 02

    Compute

    Real-time edge analytics on the tractor combined with cloud aggregation.

  3. 03

    Score

    ML regression scores acre/min efficiency and flags seeding variance.

  4. 04

    Recommend

    Parameter adjustments suggested with cost-factor weighting.

  5. 05

    Predict

    Yield forecasting and anomaly detection across the season.

Business impact

Before vs. after

MetricBeforeAfterImprovement
Seed waste reduction8–12%Material
Fuel efficiency+5–7%Sustained
Operator adoption82% in 60 daysStrong
Key outcomes

What changed

  • 8–12% reduction in seed waste
  • 5–7% fuel efficiency gain
  • Increased crop productivity
  • Predictive input planning
  • Cost-to-output improvement at scale
Capabilities

Inside the build

Real-time edge plus cloud analytics
Efficiency scoring and variance flagging
Cost-weighted recommendation engine
Yield prediction and anomaly detection
Operator dashboards with daily efficiency alerts
Talk to us

Could this work for your team?

We adapt these blueprints to your domain, data and governance constraints — typically delivering a working prototype in weeks.

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