Executive Summary
A leading North American tomato grower partnered with Altimetrik to transform yield forecasting using AI-powered automation across its 1,000-acre greenhouse operations.
By replacing manual, planner-dependent forecasting with a unified AI/ML-driven platform, the company improved forecast accuracy, reduced waste, and accelerated planning decisions.
Key Outcomes
30% Improvement in yield forecast accuracy — powered by AI/ML
20% Reduction in product waste per harvest cycle
30% Reduction in planning simulation time
30% Increase in developer productivity through AI-driven data automation
A Greenhouse Giant with Data Hidden in Plain Sight
One of the largest fresh tomato growers in North America. Over 1,000 acres of greenhouse facilities across seven plants and 700 greenhouses, producing multiple seed varieties year-round.
The Cost of Forecasting by Gut Feel
Yield forecasting relied entirely on individual planner expertise with no consistent data model. Accuracy sat at 82%, causing recurring volume surprises, product waste, and missed OTIF targets. The organisation had vast amounts of greenhouse data available but no way to put it to work.
Building an AI Engine for Yield Prediction
Altimetrik built an AI-powered forecasting platform in three layers:
- A unified data foundation consolidating greenhouse data from all seven plants into an automated pipeline that is clean, reliable input for the AI model.
- An AI/ML forecasting model trained across planting cycles, seed varieties, and historical performance. Target accuracy: 95% at week one, 90% at week six.
- A self-service platform with scenario modelling, alerts, and dashboards by putting AI-generated yield intelligence in the hands of planners, no data science support needed.
From Forecasting Uncertainty to Operational Precision
- Forecast accuracy improved by 30% across all facilities and seed varieties
- Product waste reduced by 20% per harvest cycle
- Planning simulation time cut by 30%
- Developer productivity increased by 30% through data ingestion automation
- Greenhouse capacity utilisation and operational efficiency each improved by 20%
