Miha, a data scientist at Ceneje, joined the company in March 2020 to explore business process optimization opportunities in content management, particularly through machine learning adoption. The team developed a system that uses machine learning for categorizing products on their website, which involves automatically classifying products by textual description and images. To improve this process, they considered adding another classifier, but it required careful architectural design to avoid technical debt and ensure scalability. They adopted Ray, a distributed processing framework, as the solution due to its scalability, library-agnostic model serving capabilities, and Python-first approach. The team implemented autoscaling using Ray Serve's experimental API, which initially lacked this feature, and also explored cloud cost optimization strategies. To maintain code maintainability, they utilized tools like Ray Tune for hyperparameter search and MLflow integration, allowing other teams to serve their models directly from MLflow.