Health care is the biggest concern and cautious element in the real-world scenario. These days, individuals without any age barrier are easily getting prone to ill health quickly. Health realization is increased in society to protect from serious sickness and promote wellbeing. To address this, multiple facets are to be reached. Primary facet includes quality, technology and its intervention. Timeliness is also important factor in quality. Towards moving to technology, there is a rise in automated systems. Such systems shall coordinate care, streamline workflow, and ensure that patient gets the right information at right time. Along with the technological updates, the health care platform is nowadays moving towards artificial intelligence (AI) to address health support services, with fewer delays. The aim in this work is to assist an individual with an automated system for instant service access to health-related welfare. Despite these advances, existing solutions have few flaws to meet the increased demand for reliable, real-time assistance and personalized care. This work presents a medical support chatbot, developed using the Rasa framework, which is developed to fill these gaps. Its specific requirements include to provide a 24/7 interactive platform for individuals in different roles. Healthcare providers can also use the proposed system to provide medication from anywhere in the world. A support system is designed to enhance customer services and streamline the interaction with the user by automating responses to the most frequently asked questions(FAQs), providing various communication channels, and escalating issues when necessary. The automated system is facilitated with data storage in MongoDB for patient inquiries and responses. This work details the design and functionality of the support system. This work performs a comparison analysis between the proposed system and traditional support systems and checks the performance of the proposed system. The advantages of using this proposed system are illustrated in terms of accessibility, response time, and accuracy in intent recognition. This proposed system will fill in all the gaps in communication while maintaining resource utilization in any healthcare setting with a focus on user engagement and scalability.