Case Study: a large scale agricultural player achieves more accurate yield forecasting with Altimetrik

a large scale agricultural player boosts yield forecasting accuracy by 30% with Altimetrik

The client, a large scale agricultural player, faced challenges with manual yield forecasting methods that achieved only 82% accuracy. This inadequacy negatively impacted their operational efficiency and on-time delivery performance. They partnered with Altimetrik to develop an AI-powered Data-as-a-Service platform to automate this process and improve accuracy.

Altimetrik implemented a solution that automated the data pipeline and deployed a machine learning model on the Calibo-lazsa cloud platform. This provided a single source of truth for data and a user-friendly dashboard for insights. The new system increased yield forecasting accuracy by up to 30%, reduced product waste by 20% per harvest cycle, and achieved a 30% productivity gain for developers through data ingestion automation.