Use case
Embedded tutoring
Tutors built on the lecturer's own resources answer from those sources, not from general knowledge.
The problem
General AI tools answer from the internet, not from your course. Students get answers that don't match what they are taught, or that skip the thinking altogether.
How it works
- 1
Add your resources
Lecturers add their notes, readings and slides, in the languages they teach in, to the tutor's knowledge base.
- 2
Students ask
Students get answers from those sources, with a citation to the passage each answer came from.
- 3
Practise real situations
A tutor can also play a role, such as a patient or a client, so students practise before the real thing.
- 4
See what's hard
Insights show where students struggle.
Built with
More use cases
- Gateway module support at scaleWeekly practice and feedback for large first-year modules
- The weekly learning loopSet up, complete, review the gaps, teach the gaps
- Modern assessmentPaper tests, marked against the memo in days
- Augmenting educatorsLecturers build more, and mark consistently
- Student engagement and successLink student effort to better work
- From faculty pilot to operational rolloutStart with modules, then scale to the faculty
Which module would your educators point to first?
Start with one module and a baseline. We'll show you the change before you expand.