This work presents the AIRL-Platform, an educational and research-based technological development that combines Artificial Intelligence, Internet of Things, and robotics. It fosters an adaptive and interactive learning space. Robotics and AI are considered scientific disciplines of the future and face significant barriers. These include uneven geographical access, high costs, and implementation challenges. Such issues hinder the widespread adoption of these technologies and vocational training for new students. The platform includes configurable modules and boards, all controlled by an ESP32 microcontroller. These allow simulating behaviors and performing real tasks through commands sent from the cloud. A prototype quadruped robot equipped with sensors and servomotors was implemented as a proof of concept. This forms part of an integrated virtual laboratory system that enables telemetry recording and remote experimentation. The system interfaces via MQTT (Message Queuing Telemetry Transport) to a web system developed with Flask and JavaScript. This setup allows students to interact easily through any standard browser. Additionally, the platform features an AI-based virtual tutor that guides students step by step. It covers subjects such as calculus, algebra, physics, programming, and English at different levels. The result confirms the system’s technical feasibility and scalability. Experimental results showed an average success rate of 87% in IoT communication and a usability rating of 4.6/5 from students. These findings demonstrate the platform’s technical feasibility and educational impact. Therefore, this work constitutes an important technological, educational, and social contribution. It offers a low-cost and easily replicable model applicable to schools, universities, and communities with limited resources.