Neurosymbolic AI Integration for Secure and Trustworthy Enterprise and Healthcare Search Architectures

As the volume of data in businesses and the health care sector grows fast, smart search designs have become beneficial in achieving effective information retrieval and decision making. Nevertheless, standard AI-based search engines are usually plagued by shortcomings in form of transparency, inability to reason and security flaws. Neurosymbolic Artificial Intelligence (AI) combines neural networks and symbolic reasoning, which can provide a solution to the difficulties. In this paper, the concept of neurosymbolic AI as an empowerment of secure, explainable and trustworthy search architectures in both enterprise and healthcare setting is discussed. In the study, the authors emphasize the benefits of using data-driven learning and complemented by a rule-based thinking approach that leads to more accurate results, easier interpretation, privacy, and compliance with regulatory requirements. Improved reliability of the search and ethical and secure treatment of sensitive data should be achieved within the proposed framework.