Film-style poster for the Mentornity AI for Student and Alumni Mentoring presentation

Mentornity AI forUniversities and Alumni Mentornity AI for Universities and Alumni

How university and alumni teams run a mentoring term with Mentornity AI.

English

What this presentation covers

What is Mentornity AI

An assistant that runs your program

It handles matching, follow-up, communication and reporting for you; you approve each step.

Watches the program Applications, matches, meetings
Does the work Matches, e-mails, rules, reports, certificates
You approve One click; nothing changes without you

Where you find Mentornity AI

Mentornity AI inside your admin panel

Ask it in the side panel, or press a "with AI" button where you work.

Ask in your own words

It reads the live program and answers with numbers and charts.

"With AI" buttons where you work

Applications, quiet matches, health, reports and forms each have one.

Nothing runs until you send

A button opens a ready request; credits are used only when sent.

Write with AI in the editors

E-mails, posts, events and agreements get a draft you can insert.

Ask in your own words

It reads the live program and answers with numbers and charts.

"With AI" buttons where you work

Applications, quiet matches, health, reports and forms each have one.

Nothing runs until you send

A button opens a ready request; credits are used only when sent.

Write with AI in the editors

E-mails, posts, events and agreements get a draft you can insert.

Matching

Students matched with the right alumni

It scores alumni with your rules and proposes each match as a card.

Three alumni per student

Each proposal names the rules the alumnus meets.

Rules on careers, not only cities

It proposes a rule pairing target careers with alumni sectors.

Three alumni per student

Each proposal names the rules the alumnus meets.

Rules on careers, not only cities

It proposes a rule pairing target careers with alumni sectors.

Students falling behind

Students who fall behind

Ask who has no meeting or has gone quiet, and get the names.

A list, not a count

Meetings held, booked and the last one for each student.

Quiet matches, most silent first

Days of silence, and a restart e-mail ready to approve.

A list, not a count

Meetings held, booked and the last one for each student.

Quiet matches, most silent first

Days of silence, and a restart e-mail ready to approve.

Thanking mentors

Thank mentors with real numbers

A monthly post shows what students achieved, without naming anyone.

Term end

Term end: certificates and a report

Certificates for everyone who qualifies, and a report for the faculty.

Certificates in one card

Everyone who meets the rule gets one, with an e-mail.

A report for the faculty

Students who met, meetings held and certificates, with charts.

Any report, explained

Open a report and press "Explain with AI" for its findings.

Certificates in one card

Everyone who meets the rule gets one, with an e-mail.

A report for the faculty

Students who met, meetings held and certificates, with charts.

Any report, explained

Open a report and press "Explain with AI" for its findings.

Scheduled tasks

Checks that run on a schedule

Up to five tasks per program; each run brings its proposals as cards.

A new program

Build the next program with AI

Answer a few questions in New program; its assistant then finishes the setup.

Requests to try

Requests to start with

Type one in the side panel; it reads the data itself.

"Which students have not met their mentor?" Names, meetings and the last date
"Suggest an alumnus for each unmatched student." Match cards, each with its reasons
"Write a thank-you post for mentors with this month’s numbers." A post card, no names
"Issue certificates to everyone who qualifies." One card, an e-mail to each
"Prepare the term report for the alumni office." Numbers, charts and two proposals

Advice

How to get good answers

A few habits make its proposals fit your program.

Fill in the program profile Goals, audience and tone shape every answer
Add the academic calendar to the profile Its nudges wait until exams are over
Give students small dated steps To-do lists with due dates, then a check
Start with one weekly check Add tasks one at a time, five at most
Approve or reject every card Nothing changes until you decide

Privacy and cost

Privacy, credits or your own key

The model sees aliases, and you pay with credits or your own Anthropic key.

Names stay with you

The model sees participants under aliases, never their contact details.

Credits or your own API key

With your Anthropic key, Anthropic bills you and no credit is used.

Names stay with you

The model sees participants under aliases, never their contact details.

Credits or your own API key

With your Anthropic key, Anthropic bills you and no credit is used.

Claude connector and MCP

Mentornity inside Claude for your participants

Mentors and mentees ask Claude in plain words; it books, plans and replies in Mentornity.

Claude, or any MCP assistant

They add the Mentornity connector and sign in with their usual account.

Meetings, hours and messages

Claude finds free slots, books, reschedules and drafts replies on request.

A preview before every change

Claude shows what will change; nothing happens until they say yes.

The program team decides

Claude sees only what the member sees; you can turn it off.