Overall, the entire implementation process can be broken down into several steps and always starts with defining the use cases you need the AI system for. Then, you need to gather and prepare the necessary data. Next, develop conversational flows that are tailored to various conversation scenarios. After that, train and deploy the AI model, integrating it with relevant systems currently in use. After the launch, you should monitor the performance of your AI assistant, provide ongoing support and maintenance, and ensure that it complies with regulations. Lastly, establish continued collaboration between developers, healthcare professionals, and end-users for the implementation to be a success., Intelligence at the point of conversation Enterprise-grade AI for clinical conversations—trusted by the largest healthcare systems. Measurably improving outcomes for clinicians, nurses, and revenue cycle teams at scale., Conversational AI in healthcare refers to intelligent systems that interact with patients and staff, handling tasks like answering questions, booking appointments, and even symptom checking..