Case Study: Wildlife Protection Solutions achieves scalable, reproducible camera trap research with ClearML

Wildlife Protection Solutions manages 65,000 photos a day with ClearML

Wildlife Protection Solutions (WPS), an organization empowering conservationists with technology, faced significant operational hurdles managing terabytes of camera trap data for their endangered species protection efforts. Their challenge was to efficiently process, version, and analyze this vast amount of data to build a reproducible and scalable machine learning framework for their Akili platform. They turned to the vendor ClearML to utilize its Hyperdatasets and Tasks features to overcome these obstacles.

ClearML provided the MLOps backbone for WPS's Akili platform. The solution used ClearML Hyperdatasets for agile, versioned data subsetting and storage efficiency, while ClearML Tasks automated and tracked every step of their workflow from data ingestion to model deployment. This integration created a robust, reproducible framework that meticulously links code execution to precise data versions. The result is a scalable system that processes over 65,000 photos daily, providing critical, real-time insights that are essential for thwarting poaching attempts and protecting endangered species globally.

Wildlife Protection Solutions