We worked closely with the client to architect, design, and develop a web and mobile platform for real-time data aggregation and analytics.
One of the key inputs to this platform is computer vision algorithms that we developed using deep learning and conventional techniques. These algorithms automate the detection and classification of pathogens from microscopic images with > 95% accuracy.
We built over 500 data pipelines to collect data from farms across the United States and Europe as well as US government agencies such as FDA, USDA, OSHA and others. The data existed on multiple technology platforms, websites, and file formats including PDF, CSV, XLS, and JSON. We also designed a custom data model to cater to the unique characteristics and requirements of the use case, considering factors such as food production, processing, distribution, and consumption. This platform is a powerful foundation to weave together insights and knowledge that are delivered to end-users through interactive dashboards, e-mails, and alerts.
The solution is cloud-native with automated mechanisms for scaling, code deployment and maintenance, and data security. Additionally, our QA team has written over 1,000 automated tests to ensure code quality and stable feature releases.