In the context of ML pipeline automation, what is the meaning of 'model deployment'? Consider a scenario where a company has developed a machine learning model to predict customer churn and now wants to integrate this model into their live customer relationship management (CRM) system to provide real-time predictions. The company is concerned about ensuring the model's predictions are accurate, the system is scalable to handle thousands of requests per second, and the deployment process is cost-effective. Given these constraints, which of the following best describes the meaning of 'model deployment' in this scenario? (Choose one correct option)