The rECGnition Web Server presents an innovative and accessible platform that includes a powerful inference server and a straightforward, no-code interface. Designed to perform comprehensive multimodal ECG data analysis through the rECGnition methodology, this server utilizes a multi-modal deep learning architecture that effectively integrates patient demographics with ECG morphological features. This integration is crucial for enhancing diagnostic precision and adaptability in clinical settings. By incorporating key patient characteristics such as age, gender, and medical history—factors known to significantly influence ECG signals—the platform enables more personalized and accurate ECG interpretations. Furthermore, it empowers medical practitioners by allowing them to configure and conduct ECG analyses without the need for programming skills, thereby democratizing access to advanced diagnostic tools.