Purpose: This study presents the design, implementation, and evaluation of Lectoentreno, a web-based software developed to enhance reading comprehension in university students through embodied cognition strategies and text manipulation. The research addresses the global decline in literacy competencies, which is particularly critical in the Chilean context. Methodology: The software architecture follows a Model-View-Controller (MVC) pattern, integrating a Vue.js frontend and a Laravel back-end. A 15-session intervention program was conducted with university students. The impact was assessed through the System Usability Scale (SUS) and electrophysiological measures, specifically focusing on the modulation of N400 and post-N400 Event-Related Potentials (ERPs) during reading tasks. Results: Quantitative analysis revealed high usability scores (SUS = 89.3 for professors; 81.25 for students). Electrophysiological data indicated that the intervention effectively modulated neural activity in the N400 and post-N400 windows, particularly in conditions requiring high inferential effort. Compared to traditional methods, the experimental group showed more efficient construction and updating of mental models. Conclusion: Lectoentreno proves to be a superior tool for advanced reading instruction by successfully modifying neurocognitive processes associated to reading comprehension. By aligning pedagogical practices with modern neuroscientific evidence, the system provides a robust framework for monitoring student progress and fostering deep learning in higher education.