Running machine learning (ML) models in a hybrid setup, where existing models are executed locally and their results are sent to the cloud, can offer several benefits in terms of flexibility, scalability, and cost-effectiveness. This approach leverages the strengths of both local and cloud-based computing resources, allowing organizations to utilize their existing infrastructure while taking