Crop Yield Prediction Through AI

A large-scale agricultural producer manages crops across multiple estates and growing regions, each with different ages and cultivars. Praelexis built an end-to-end machine learning system to forecast yield with far more consistency than manual estimation allowed.

The client needed accurate forecasts to plan cut dates, harvest volumes, and deliveries to the mill well ahead of time.

Praelexis combined the client's historical records with multiple external data sources, rather than relying on farm records alone. An interpretable model produces a forecast and a confidence score for each prediction, tailored to the different crops and growing conditions across the business. The model runs in live production, with ongoing monitoring and retraining as new data arrives.