In this presentation we will provide a system overview, describing our methods for creating a forecasting tool that generates daily reports and has automated quarterly model training, evaluation, and deployment to production. This talk will touch on Python in production, DevOps, MLOps, and process automation. We will describe the interaction between all of these pieces, our layers of modeling, and how we have set up continuous integration and continuous deployment (CI/CD) for pull requests and build and release pipelines and for automated model training, evaluation, and deployment to our development and production environments. This presentation will focus on system design and implementation, not on modeling or financial analytics.