Solstice Agriculture: Advanced Data Strategy and Precision Predictive Analytics

The challenge

Solstice Agriculture manages over 40,000 hectares of mixed cropping across three regions. The operation generated enormous volumes of data, soil moisture probes, weather stations, satellite imagery, drone surveys, and machinery telemetry, but none of it was connected. Agronomists were making planting, irrigation, and fertilisation decisions based on experience and gut feel, occasionally cross-referencing a spreadsheet of last season's results. The data existed to make better decisions, but it was locked in silos.

The real problem was timing. By the time a field showed visible signs of water stress or nutrient deficiency, the window for cost-effective intervention had already closed. Pest incursions were spotted during scheduled inspections rather than detected early. Solstice's leadership knew they were leaving yield and margin on the table, but lacked a coherent data strategy to turn raw sensor feeds into actionable intelligence.

What we built

A unified data platform and predictive analytics engine that ingests all farm data sources and delivers field-level forecasts and recommendations:

• Centralised data lake: soil sensors, weather feeds, satellite imagery, drone captures, and machinery GPS logs all flow into a single normalised data layer, updated continuously and accessible from one interface
• Yield prediction models: machine learning models trained on three seasons of historical data forecast expected yield per paddock, updated weekly as new satellite and sensor data arrives, giving agronomists a rolling forward view
• Water stress and pest risk alerts: the platform detects early indicators of moisture deficit and pest pressure from multispectral imagery and microclimate data, issuing alerts days before visual symptoms appear
• Fertilisation optimisation: variable-rate application maps generated from soil chemistry data and growth-stage modelling, replacing blanket application schedules with precision recommendations
• Seasonal planning dashboard: a decision-support interface that combines forecasts, input costs, and commodity pricing to help the operations team plan planting rotations and input procurement

Technology

Unified data ingestion pipeline connecting IoT sensors, satellite feeds, weather APIs, and machinery telemetry into a cloud-hosted data lake. Machine learning models for yield forecasting, stress detection, and variable-rate optimisation, retrained seasonally as new ground-truth data becomes available. We run it on Solstice's infrastructure and retrain the models each season, and Solstice keeps full ownership of its data.