The publication explores the development of the Augmented Medication Risk Score (AUGMERIS) calculator, a web application supported by artificial intelligence, designed to automate the evaluation of medication therapies with the Danish Medication Risk Score (MERIS) method. It is a tool that assesses drug combinations and kidney function in estimated glomerular filtration rate (eGFR), which helps clinical pharmacists identify high-risk patients. To overcome the problem of processing unstructured electronic health records (EHRs), a hybrid text processing model was created by combining rigorous algorithms and Generative Pre-trained Transformer (GPT) technology, which was integrated into a web application along with an automated risk calculation programme. Our objective was to develop and test a globally accessible calculator application with the validation of performance on poor-quality data. Despite the validation limitations, the text processing function serves the application satisfactorily. The AUGMERIS web app is built with Python 3 and shared globally by Streamlit. Volunteer testers from eight different countries performed a total of 383 trial calculations. The application has the potential to improve global pharmacotherapy by identifying patients requiring medication reviews. Its wider adoption might enhance patient safety and optimize treatments in a variety of healthcare systems.