ThoraxAI is an advanced artificial intelligence-powered system designed for the automated detection and diagnosis of thoracic diseases using chest X-ray images. Developed with the goal of addressing the global shortage of radiologists and the rising demand for rapid and accurate diagnostics, ThoraxAI leverages deep learning using convolutional neural networks (CNNs) to analyze medical imaging data with high precision. The system is trained on two large-scale, annotated chest X-ray datasets, namely NIH ChestX-ray14 and CheXpert, enabling it to recognize a wide spectrum of thoracic abnormalities, including pneumonia, tuberculosis, lung nodules, cardiomegaly, and pleural effusion. Through image preprocessing, feature extraction, and multi-label classification, ThoraxAI provides interpretable diagnostic outputs, including heatmaps and confidence scores, to assist clinicians in decision-making. ThoraxAI is designed for integration into hospital radiology workflows, allowing real-time triage of urgent cases, reduction in diagnostic errors, and acceleration of reporting times. Its modular architecture supports both on-premise deployment in medical institutions and scalable cloud-based solutions for remote or underserved regions. Beyond diagnosis, ThoraxAI incorporates explainable AI components to enhance trust and usability among healthcare professionals by offering visual explanations of its predictions. By combining technological innovation with practical clinical utility, ThoraxAI addresses key challenges in global healthcare, especially in low-resource settings by offering a scalable, efficient, and cost-effective diagnostic aid that empowers radiologists, reduces workload, and ultimately improves patient outcomes.