Build 'ScholarGuard AI'—a governed AI inference gateway specifically for higher education. This platform acts as a middleware between university LMS (Learning Management Systems) and foundational model providers. It ingests the latest government safety guidelines and 'slow-roll' restrictions in real-time, dynamically filtering model outputs and restricting access to specific model capabilities based on the user's role (e.g., Undergraduate vs. PhD Researcher). It provides a 'Federal Compliance Log' for every query, ensuring the university can prove to auditors that no prohibited model features were accessed by students.

The federal government is actively intervening in AI release cycles, creating a bottleneck for universities and research institutions that rely on cutting-edge models for curriculum and research. When models are 'slow-rolled' or restricted, academic programs face immediate obsolescence in their teaching materials. Furthermore, using restricted models in a classroom setting exposes universities to federal compliance risks if the model generates harmful content or violates new executive orders. There is no 'Academic Safe Zone' infrastructure that allows universities to access advanced AI capabilities while guaranteeing strict adherence to government safety mandates.