How TUEL brings together fragmented AI tools into one verifiable, compliant platform that institutions can trust.
TUEL Team
Product
Higher education institutions face a growing challenge: AI tools are proliferating across campus, each with its own data silo, compliance gaps, and administrative overhead. Faculty members adopt different tutoring assistants. IT struggles to maintain security across disconnected systems. Students receive inconsistent AI experiences depending on which class they take.
Most universities today run multiple AI tools simultaneously. A chemistry department might use one AI tutor, while the business school uses another. Each tool requires separate vendor agreements, security reviews, and faculty training. The result is operational complexity that scales with every new adoption.
Beyond logistics, fragmentation creates compliance risks. When student data flows through multiple AI systems, tracking data residency and ensuring FERPA compliance becomes nearly impossible. Institutions need visibility into how AI interacts with their students, but disconnected tools make centralized oversight difficult.
TUEL addresses this by providing a unified layer that sits between your institution and AI capabilities. Rather than replacing existing tools, TUEL integrates them into a single, auditable platform. Every AI interaction passes through TUEL, which means every response can be traced, every output verified, and every session logged.
What this means for your institution:
Educational AI adoption stalls when administrators cannot verify what the AI actually does. TUEL solves this with source citations on every response. When a student asks a question, the AI grounds its answer in uploaded course materials and shows exactly which textbook page, lecture slide, or syllabus section informed the response.
“We needed to know that the AI was teaching from our curriculum, not making things up. TUEL gave us that confidence with citations we could actually verify.”
TUEL offers pilot programs designed for institutional evaluation. Start with a single department, measure outcomes, and expand based on data. Our pilot at Elon University demonstrated 95% faculty satisfaction and zero hallucination incidents across 9.5 million tokens of student interactions.
Ready to see verified AI for learning in action? Request a demo with your own course materials.
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