Research
Research that ships
We study applied AI where it is actually used, so every finding comes with evidence from real people and real work.
What we study
Our research happens inside working products, with real users and real constraints. These are the questions we keep returning to.
AI in how people learn
Course design, practice and support built around how working professionals learn, with faculty in control of the material.
Accessible and on-brand by default
How much of accessibility and design review a machine can do safely, and where human judgment has to stay.
Workforce and skill signals
Turning employer needs into skill maps, assessments and evidence that programs and learners can act on.
Early research, partners welcome
Nothing ships until it passes four checks
Fig. 1The same signal, cleaner after each check
01
Accuracy
Does it give the right answer, and say so when it does not know?
02
Accessibility
Can everyone use it, with WCAG 2.1 AA as the floor?
03
Privacy
Does it use only the data it should, and keep it where it belongs?
04
Cost and time
Is it better than the old way for the people who do the work?
Questions on the board
- Q01Which admitted students need a nudge this week?
- Q02Can every course file pass accessibility before launch?
- Q03What should a student learn next to land the role they want?
- Q04How long does it really take to build a course?
- Q05Can a rough deck be on brand by morning?
- Q06Which skills are employers asking for next?
- Q07Where does a learner get stuck, and why?
- Q08Can an assistant answer from approved program data only?
Faculty, researchers and partners: study it with us
Bring a method, a dataset or an open question. We bring working systems, real users and a student team.