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Use case · Local authority

In September, student services receive a whole year's questions in two weeks

22,000 students, seven faculties, and a start of year where registrations, grants, cards and timetables all land at once. Student services receive 9,000 emails in two weeks, led by “where does my registration stand”.

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The starting point

The question is simple, it is the volume that overflows

Nine questions out of ten have a written answer somewhere — on the intranet, in a PDF, in an email from last year. They arrive in seven inboxes, with no priority, and the student whose file is genuinely blocked waits behind those asking for a timetable.

  • 9,000 emails in two weeks, across seven inboxes
  • Nine questions out of ten already have a published answer
  • No priority between a timetable and a blocked file
  • A student services appointment is obtained by queuing

What we put in place

Absorb the peak without hiring for two weeks

  1. 01

    The help center becomes the reference

    Each faculty's answers are written once, in a published knowledge base. The student finds them, and the AI agent reads the same thing.

  2. 02

    The AI agent takes the first line

    On the website and the intranet, it answers start-of-year questions at any hour, and creates a ticket for a human when the case is individual — with the student number and the context.

  3. 03

    Requests become tickets

    Every request is a ticket, sorted by faculty and by type, with a priority: a blocked file comes before a timetable. Response times are visible.

  4. 04

    Student services appointments are booked online

    By reason and by faculty, with an SMS reminder. The queue outside the office becomes a list of slots.

What it shifts

What the setup aims for

≈ 60%
of start-of-year questions resolved without an agent
< 48 h
target response time on a blocked file, even in September
7 → 1
inboxes
0
physical queues for an appointment

FAQ

Frequently asked questions

Can the AI agent access the student's file?

Not by default: it answers from published content. An individual case becomes a ticket handled by an agent, who looks at the file in the student records system.

Can each faculty have its own answers?

Yes. The knowledge base is structured by faculty, and the AI agent answers according to the student's faculty when it knows it.

Do the tickets connect to the university's information system?

Through the API and the student number. The ticket carries the identifier, and the agent opens the file in one click.

And GDPR, for students who are sometimes minors?

Data hosted in the European Union, access by department, retention period set by the institution. The chat asks for nothing more than what it needs to answer.

Another question? Write to us — a human will answer.

Before you decide

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Comparisons

Coming from somewhere else? The migration is gentle

Contacts, companies, opportunities, tasks, segments and email templates come across from Brevo, HubSpot or an export. Keep your old tool as long as you need: nothing forces a big-bang switch, and nothing is deleted on your side.

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