In the rapidly evolving landscape of artificial intelligence, where systems generate vast quantities of data, predictions, and decisions with unprecedented speed and confidence, a critical gap has emerged: the need for mechanisms that ensure these outputs are not only powerful but also correct, trustworthy, and aligned with real-world constraints.