Case Study: DTN accelerates machine learning workflows with Metaflow from Outerbounds

How DTN Transformed Productivity

DTN, a leading provider of data-driven insights for agriculture, weather, and fuel logistics, faced challenges with an inefficient, homegrown data science infrastructure. Docker rebuilds, difficult debugging, and high maintenance overhead, which hindered their data scientists' productivity. They turned to Outerbounds and implemented the open-source framework Metaflow to address these issues.

By adopting Out from over a month to less than a week, and cut operational bottlenecks by 50%, allowing them to manage twice as many models in production.

DTN

Tyler Potts

Data Science Platform Lead