Case Study: Four Growers cuts annotation time by 50% with Encord

Transforming Fruit and Vegetable Harvesting & Analytics with Computer Vision

Four Growers is an automated harvesting and analytics company building computer vision-powered robots to help greenhouse growers reduce waste and improve produce quality. The team needed a better way to create and manage training data for its models, but public datasets were scarce and its manual annotation workflow was slow, fragmented, and time-consuming. Encord helped Four Growers with data labeling through Encord Annotate and related tooling.

Using Encord’s platform and annotators, Four Growers streamlined dataset creation, automated much of the labeling process, and reduced the burden of consolidating work from multiple external annotators. The company also began using Encord Active to test and evaluate models more effectively. As a result, Encord cut the time Four Growers spent providing feedback on imagery by more than half, reducing a task that previously took about 2 hours to roughly 30 minutes.

Four Growers

Mira Murali

Computer Vision Engineer