MentorFeed gives lecturers and teaching fellows an AI workspace to review proposals, chapters, ethics applications and theses in minutes — so a heavy supervision load stops taking over the week.
One workspace for every research discipline
Set each supervisee up once. After that, their drafts flow in from Google Drive and come back as structured feedback — no re-uploading, no copy-paste, no late nights.
Add the students you supervise with their field, degree level and thesis title. That's all MentorFeed needs to adapt to each discipline — students never log in here.
Point MentorFeed at each student's shared Google Drive folder — read-only. Drafts and cited PDFs sync into their library automatically.
It reads the draft against the student's own sources and the standards of their field — proposal, chapter, ethics form or full thesis.
Prioritised, actionable notes stream in live, download as a formatted Word report, and are saved to the student's progress history.
every week, off your plate
from draft to structured feedback
tracked from one dashboard
One tool from first proposal to final defense — reviewing in each student's own discipline.
Aims, questions, methods and gaps — sharpened before the project locks in.
Section-by-section feedback on drafts, ranked P1 / P2 so students know what to fix first.
Consent, data handling and safeguards checked against requirements before submission.
A rubric-based evaluation of the completed thesis, rendered as a table and a report.
Before a student submits to the ethics committee, MentorFeed flags the gaps reviewers always catch — so the application clears in one pass, not three.
MentorFeed pulls every in-text citation and the claim it's attached to, matches it against the student's own reference library, and checks whether the source really backs the claim — then suggests stronger citations to add.
A methodology chapter in Chemistry is judged on reproducibility and controls; in Law, on doctrinal reasoning; in Business/IT, on constructs and validity. MentorFeed sets the persona and rubric from the student's registered discipline — no prompt engineering required.
Small and mid-sized universities use MentorFeed to help their lecturers and teaching fellows supervise more students well — without the workload spiralling.
Supervisors see only their own students; admins see the whole department. Every review is logged.
Every proposal, chapter and thesis is held to the same rubric — new supervisors included.
Students iterate in days, not months — freeing supervisors for the mentoring that matters.
MentorFeed runs entirely on infrastructure you control — so unpublished research and student records stay inside the university, never on someone else's cloud. Nothing to explain to a data-protection committee.
MentorFeed installs on a machine you control. The database and every document live on your infrastructure — not a third-party SaaS.
Pair it with a self-hosted model, so student drafts and feedback are never sent to any external AI provider.
Only the application is reachable, over an encrypted connection. The database is never on the open internet.
Full control of records and backups — export or delete anytime. Built to support your GDPR / FERPA obligations.
Add a supervisee, connect their Drive, and let MentorFeed handle the mechanics of feedback — so you can spend your time on the mentoring that matters.
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