Course-grounded responses
Answers trace back to approved course materials, not generic internet chat.
Proven at Elon University
Verified AI for higher education, grounded in your course materials.
TUEL is built so responses can cite approved course materials, deployments can be configured around institutional policies, and buyers can review a live higher-ed proof point before rollout.
Every response is grounded in approved course materials. Every deployment is configured around institutional policies, branding, and academic-integrity goals.
Spring 2026 Elon deployment
202
active users
Spring 2026 deployment cohort
88%
voluntary adoption
students chose to use the tutor
94%
average exam score
among engaged weekly users
Institutional policies
Brand voice, integrity mode, and escalation rules enforced at deployment.
Verified source trace
Students can see where each answer came from instead of trusting black-box output.
Real student-facing Elon AI deployment, not a mockup.
See live proofInstitutional proof rail
Evidence for institutional adoption.
TUEL is designed for the procurement questions universities actually ask: what is the system grounded in, who controls it, how is it audited, and what outcomes can you show after launch.
Launch partner
Live deployment with course-specific tutors, institutional controls, and documented student outcomes.
Institution-branded deploymentSpring 2026 proof point
- Active users
- 202
- Adoption
- 88%
- Exam average
- 94%
Faculty-configured behavior
Controls for persona, integrity mode, tools, and assistant boundaries per course.
Auditability and oversight
Operational visibility, action logging, and deployment telemetry for institutional teams.
Institution-owned deployment
FERPA-aligned review materials, institution-owned configuration, and rollout support from pilot to scale.
Institutional controls are part of the product
Branding, guardrails, escalation logic, and deployment policies are configured into each implementation instead of bolted on after launch.
course-grounded • auditable • policy-aware
Live deployment proof
Elon AI proves the platform. TUEL is the system behind it.
Elon University deployed TUEL-powered course assistants in December 2025. By Spring 2026, 88% of students voluntarily adopted the tutor, averaging 94% on exams. TUEL is now ready to bring this model to other institutions.
“What stood out to me most is that 88% of my students voluntarily used the Elon AI Tutor as part of their study routine. When you hand your students a thoughtfully designed AI tutor along with clearly described instructions on how to effectively use it, they utilize it as a learning aid rather than a learning shortcut.”
Dr. Mustafa Akben
Assistant Professor of Management and Director of Artificial Intelligence Integration
Elon University
Researcher and faculty leader focused on deep learning, generative AI, institutional readiness, and organizational behavior.
Academic outcomes
202
active users
Spring 2026 deployment cohort
88%
voluntary adoption
students chose to use the tutor
94%
average exam score
among engaged weekly users
96%
student satisfaction
73 / 76 positive ratings
Operational telemetry
622
sessions
Last 90 days
72.2M
tokens processed
Last 90 days
204
total users
live production footprint
2%
error rate
for the reporting window
The live deployment is currently tracking 622 sessions, 72.2M tokens, 204 total users, and a 2% error rate in the most recent reporting window.
Live sample demo
Try the student experience. Then decide if you want the institutional walkthrough.
The demo stays ungated so buyers can feel the product before they fill out a form. When you want to see TUEL configured around your syllabus, policies, and brand, that is the next step.
Try a real sample course experience
Ask a question, inspect the response style, and see how the tutor behaves in a course-grounded student workflow.
Try it now: ask a Biology question and inspect how the response cites course material.
This sample course is public. Your institutional walkthrough is private.
Next step
Want to see this with your syllabus?
We will map the product story to your institution, show the faculty and admin surfaces, and scope a pilot path if there is mutual fit.
Real product gallery
Real interfaces that show how TUEL works for students, faculty, and institutional teams.
The strongest proof on this site is product proof. These are real TUEL-powered surfaces from the Elon deployment story, not decorative abstractions.
For students
Course-grounded tutoring with visible source citations
A live Elon AI chat surface showing course-specific assistance, interactive tools, and responses grounded in class materials.
For faculty
Faculty decide which tools, modes, and behaviors each course can use
A real teacher configuration surface from Elon AI showing no-code feature toggles and course-specific control before launch.
For admins and IT
Operational oversight with deployment telemetry and auditability
Institutional teams get visibility into sessions, tokens, users, errors, and system health for production rollouts.
Why institutions choose TUEL
A sharper alternative to generic AI chat and legacy point solutions.
TUEL is designed for universities that want credible AI support for learning without sacrificing governance, pedagogy, or institutional fit.
01
It starts from course truth, not model confidence
Students see where answers came from. Faculty know what the tutor is grounded in. Administrators get a cleaner trust story from day one.
02
It supports teaching without replacing academic judgment
Integrity-aware interactions, Socratic tutoring patterns, and configurable tools help institutions support learning without inviting shortcut behavior.
03
It gives institutional teams a rollout model they can defend
TUEL is built for pilots, internal review, governance conversations, and cross-functional adoption. It is not a one-size-fits-all chatbot.
04
It already has a live higher-ed proof point
Elon AI is not a mock launch. It gives TUEL a concrete operating example for what deployment, measurement, and product quality can look like.
Institution-ready controls
The controls universities need before AI becomes rollout-ready.
TUEL is designed for the evaluation criteria that matter in higher education: academic integrity, faculty control, privacy, integration, and measurable rollout outcomes.
Institution-owned data
Your university controls branding, content boundaries, data ownership, and launch decisions.
Pilot-to-scale support
Start with one department, measure impact, and expand with onboarding and implementation support.
Faculty control at the course level
Configure assistant behavior by course, choose supported tools, and align the tutor to pedagogy instead of generic chat behavior.
Governance for institutional risk and compliance
Role-scoped access, integrity-aware modes, review materials, and visibility into how the system is configured for launch.
Operational visibility for adoption and support
Track usage, student engagement, and system health so pilots can be evaluated with evidence, not anecdotes.
Integrations and deployment fit
TUEL is designed to fit existing university stacks and rollout patterns instead of forcing teams into a generic AI adoption model.
Canvas reviewBlackboard reviewBrightspace reviewMoodle reviewLTI planningSSO planningInstitution brandingDepartment pilots
Common questions
Questions institutional teams ask before moving forward.
How is TUEL different from a generic AI chatbot?
TUEL is built around course-grounded responses, faculty control, and institutional governance. It is designed for universities that need verified outputs, not open-ended internet chat.
Can faculty control what the assistant does in each course?
Yes. Faculty can configure behavior, tools, integrity settings, and assistant guidance patterns per course so the product supports their teaching model.
How do you handle compliance and institutional risk?
TUEL is positioned for FERPA-aligned deployment review, institutional data ownership conversations, audit visibility, and role-based oversight. We treat rollout as an institutional implementation, not a consumer app install.
What does the demo process look like for a university?
We start with an institutional walkthrough, show live TUEL-powered product surfaces, and can scope a pilot around your syllabus, course policies, and launch goals.
Do we have to roll this out campus-wide immediately?
No. Most teams should start with a focused pilot, measure adoption and outcomes, then expand based on real data and stakeholder confidence.
Request demo
Ready to scope TUEL for your institution?
Tell us where you are in the evaluation process. We will respond with the right next step, whether that is a tailored walkthrough, a pilot discussion, or a deeper product review with faculty and IT stakeholders.
Institutional walkthrough
We tailor the conversation to your courses, policies, and launch goals.
Pilot recommendation
If there is a fit, we outline a scoped pilot path instead of pushing a campus-wide jump.
Fast follow-up
Typical response time is within one business day from an institutional email request.
Book an AI workshop or training
Tell us about your team, preferred format, and what outcomes matter most. We will follow up within one business day with a recommended program.