Case Study: IntelinAir achieves faster, more efficient crop intelligence with Activeloop

IntelinAir faster AgriTech with aerial machine learning data pipelines

Intelinair, a leading crop intelligence company in agriculture, faced the significant challenge of processing and analyzing 1.5 petabytes of complex aerial imagery and agricultural data. Their data scientists were spending over half their time on data preparation instead of model building, and they needed a scalable solution to manage their massive, multi-modal datasets. To overcome this, they partnered with Activeloop.

Activeloop implemented its Deep Lake database for AI, providing Intelinair with scalable, plug-and-play data pipelines. This solution automated data ingestion and preprocessing, unified diverse data types, and enabled efficient streaming to deep learning frameworks. The results for Intelinair included a 50% reduction in compute and storage costs, 30% less data storage required, and a 12% higher model accuracy, allowing their team to focus on developing high-quality models.

Intelinair

Jennifer Hobbs

Director, Machine Learning