Global Battery Company Problem
A global energy company had several teams using disparate methods and resources to accomplish very similar tasks. One team had a data modeling pipeline for daily bidding predictions in a regional market. It failed three to five times per week, required daily manual uploads, lacked data validation, had no pipeline infrastructure, and algorithm modifications were difficult to test and implement.
Solution
OpenTeams Open Source Architect built a data pipeline to connect the machines and CRMs. They centralized the data and built dashboards and tools to help the engineers monitor and control the assembly line.
Outcome
The outcome was an example of MLOps best practices for all of their teams to adopt. It reduces ETL and modeling errors and makes scaling, model experimentation, and production deployment easy.