Case Study: Hummingbird Technologies achieves faster, scalable AI-driven crop analytics with CloudFactory

CloudFactory Helps Hummingbird Technologies Farm for the Future

Hummingbird Technologies is an AI-driven crop analytics company that uses machine learning on drone and satellite imagery to help farmers increase yields, optimize chemical inputs, and farm more sustainably. Their challenge was massive, domain-specific image labeling: building and updating dozens of crop-specific ML models required large volumes of accurately annotated data, but in‑house annotation was too slow and agronomist time was scarce. To solve this, Hummingbird engaged CloudFactory for scalable annotation support.

CloudFactory provided a dedicated team of trained annotators working in a tight feedback loop with Hummingbird’s agronomists and data scientists, using pre-annotation from existing models and iterative corrections to boost throughput. That partnership enabled large projects like lettuce plant sizing, freed internal data scientists from months of labeling (supporting 400+ hours of annotation), sped model retraining to days for seasonal changes, and helped Hummingbird scale development of its high‑accuracy products—contributing to their portfolio of ~70 models at 90%+ accuracy and the customer benefits (typically 20–30% improved agrochemical efficiency).

Hummingbird Technologies

Francois Lemarchand

Senior Data Scientist