An artificial intelligence system represents a set of technologies and algorithms designed to imitate the cognitive processes of human beings, such as language understanding, pattern recognition, reasoning and learning. These systems are capable of processing vast amounts of data, learning from past experiences and improving their performance over time, adapting to new situations and requirements. The purpose of an artificial intelligence system is to perform tasks that traditionally require human intelligence, from providing simple answers to questions to complex problem-solving and decision-making. Blockchain is an emerging technology widely adopted across various sectors that facilitates the secure transfer of information between different participants. This ensures data integrity and confidentiality, eliminating the risk of breach or interception by unauthorised external entities. The implementation of blockchain technology in the medical field paves the way for revolutionary solutions, facilitating the efficient and secure exchange of patient data between different entities such as hospitals, testing laboratories, pharmaceutical companies and healthcare professionals. This paper explores the integration of artificial intelligence technology with blockchain to develop a system that offers significant advantages in medical diagnostics. The proposed system minimises the risk of incorrect diagnosis by providing the possibility to seek additional consultations from various specialists in the medical sector. The system also allows access to a prompt diagnosis through an integrated chat service, supported by artificial intelligence, which provides quick and accurate answers. Data storage security ensures that only authorised doctors can access patient information regardless of geographic restrictions. This guarantees efficient interconnectivity, flexibility, and robust data protection. The system provides an intuitive user interface accessible through a web platform. Here, patients can register by filling out a simple form, and the data entered is collected and rigorously protected by blockchain technology. Once registered in the system, users benefit from the platform’s facilities, having the opportunity to communicate with the medical staff via email and chat assisted by specialised medical personnel. Alternatively, they can opt for a quick and accurate diagnosis through dialogue with the artificial intelligence assistant, available in a dedicated chat. This multi-functional approach underscores the system’s commitment to patient accessibility and security, while offering flexibility in choosing the consultation and diagnostic method. In conclusion, the integration of this innovative technology into the existing medical infrastructure is not only possible, but also advisable. This would not only enable secure and rapid access to patient data by healthcare professionals irrespective of location, but also improve diagnostic accuracy through enhanced collaboration between specialists and advanced artificial intelligence support. In addition, the proposed system offers the possibility of a prompt diagnosis through an artificial intelligence-assisted chat service, making a significant contribution to the efficiency and personalisation of medical care.