A degree says what your students studied. Cadra shows what they can do with AI.
Score a cohort on the tasks industry hires for, then give every student a plan and the time to act on it.
Illustration: a sample Cadra report cycling through a student capability profile, a per-student roadmap, a cohort baseline, and term-over-term movement.
Employers are hiring for AI capability. Transcripts don't show it.
Every graduate now claims AI fluency. Almost none can prove it.
Claims outrun proof
Students list AI tools on a CV. Employers have no way to tell who actually works well with them.
Coursework isn't the job
Assignments are graded on the output. Industry cares how the work got done, with what judgment.
The gap surfaces too late
Most students discover what they're missing during placement season, when there's no time to fix it.
EU AI Act, Article 4: organisations must ensure AI literacy in their workforce. Graduates who can demonstrate it are easier to hire.
"AI skills" is not one skill.
Building AI systems and working with AI are different jobs. Cadra scores them separately.
Build the AI
CS, Data Science, and Engineering students heading into AI Engineer, ML Engineer, Data Scientist, and Data Engineer roles.
Can they build and ship an AI system that holds up?
How they design the system, evaluate it, handle cost and latency, debug it, and tie the build to the business constraint.
Work AI-natively
MBA, business analytics, commerce, and ops-track students heading into analyst, operations, sales, and product roles.
Are they measurably better at the work because of AI?
How they frame the problem, check what the AI gives back, decide when not to use it, and how good the decision is for the time spent.
One cohort is judged on what they can build. The other on how well they think with AI in the loop. A single generic test measures neither well.
It runs across a semester, not in one sitting.
Baseline
Students work through tasks built for their track, and Cadra records how they got there.
RECORDED AS THEY WORKRoadmap
Each student sees where they are strong and where they are short, with training aimed at what they got wrong.
PER STUDENTBuild
Students build real things they can show. A second score at the end shows what changed.
REAL WORKEvidence your placement office and your employers can both use.
A capability profile they can show
Scored against the rubric the industry hires on, and backed by the work itself.
Cohort benchmark
Where the cohort stands by track, early enough in the year to act on it.
A clear roadmap
What to fix, in what order, with enough runway before placement season to actually fix it.
Curriculum signal
Which gaps are systemic and worth teaching, and which are individual and worth coaching.
Placement readiness
Capability that stands up in an interview, built on tasks modelled on the real job.
Movement you can show
Re-baselining across a term produces a before and after, so progress is visible.
Let's talk about your cohort.
A short conversation about which programmes to start with, what the scenarios would look like, and what the cohort report would tell you.