AI in education that handles the back office
Custom AI for admissions and enrolment operations, student support, grading assistance, and records, built on your SIS and LMS with FERPA-safe data handling.
How it works
Enrolment teams open the season with a shared inbox nobody can clear and a stack of transcripts to evaluate by hand, one course equivalency at a time. Meanwhile the SIS, the LMS, and the financial aid system each hold a different piece of the same student and none of them talk to each other. We build AI that connects those systems and takes over the repetitive operational work, so staff spend their time on the students who need a person rather than on data entry.
Admissions and enrolment operations
Applications arrive complete, verified, and summarized instead of sitting in a queue waiting for manual review.
- Reads transcripts and maps course equivalencies against your catalogue
- Verifies credentials and flags documents that need human eyes
- Chases missing items automatically until the file is complete
- Hands reviewers a decision-ready summary with the evidence attached
Student support that answers at 11pm
Tier-one questions about deadlines, aid, registration, and holds get answered from your real systems, not a static FAQ.
- Grounded in your SIS, LMS, and policy documents, with links to the source
- Answers account-specific questions after verified sign-in
- Escalates to staff with full context when the answer needs a human
- Handles the languages your applicant pool actually speaks
Student data handling your registrar will sign off on
FERPA and directory-information rules are enforced in the system itself, not left to staff discretion.
- Role-based access mirroring legitimate educational interest
- Records stay in your environment, never used to train external models
- Full audit trail of every record accessed and every answer given
- Consent, disclosure logging, and parent-versus-student access handled by rule
Where teams use it
Built for real revenue work.
Instructors grading 300-student sections
AI drafts rubric-aligned feedback and flags likely misconceptions across the cohort. The instructor edits and assigns the grade, so students get comments in days instead of at the end of term.
Registrar offices buried in routine requests
Transcript requests, enrolment verifications, and records updates are validated, processed, and logged automatically, with only the exceptions and legal holds routed to staff.
Advising teams looking for at-risk students earlier
Signals from the LMS, attendance, and the SIS combine into an early alert an advisor can act on in week four, with the reasons shown so the outreach is specific rather than generic.
“Our reviewers used to spend the first hour of every file just checking whether it was complete. That step is gone, and the transcript evaluation now arrives with the equivalencies already mapped and sourced.”
FAQ
Questions, answered.
How is AI used in education outside the classroom?
Most of the measurable value sits in operations: application and transcript processing, credential verification, enrolment follow-up, tier-one student questions, records and registrar workflows, feedback drafting, and early-alert signals for advising. These are repetitive, deadline-driven tasks that consume staff capacity without requiring professional judgment on every instance.
Is AI in education FERPA compliant?
It can be, provided student records never leave systems you control and access follows the legitimate-educational-interest standard. We deploy inside your environment, enforce role-based permissions in the retrieval layer, log every record access for audit, and contractually prohibit student data from being used to train any external model. Vendor arrangements are structured under the school official exception with a written agreement.
Will AI grade student work automatically?
Not unilaterally, and we would advise against it. The AI drafts rubric-aligned feedback and highlights patterns across a cohort; the instructor reviews, edits, and owns the grade. That keeps academic judgment with the educator while removing the mechanical part of marking, which is where the hours actually go.
How long does it take to build custom AI for a school or university?
A first workflow typically goes live in 4 to 12 weeks, and we usually start with one, admissions document processing or student support, rather than a campus-wide programme. It is scoped as a fixed project against your SIS and LMS, and you own the resulting platform and code, so it does not become a per-student subscription that grows every year.
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