Scan the cohort roster for at-risk and disengaged learners
Autonomously monitors engagement and progress signals across the full cohort roster and surfaces a ranked list of learners who warrant a personal nudge.
In / outCohort engagement and progress data (logins, submissions, completions) → ranked at-risk list with risk signals per learner
You might say…
“Someone dropped off three weeks ago and I only noticed when they didn't submit. I need the system to tell me before it's too late.”
What it does
Autonomously monitors engagement and progress signals across the roster (missed submissions, login gaps, falling behind pace) and surfaces a ranked list of learners who warrant a personal nudge. Runs on a schedule across the whole cohort rather than per-learner, which is why it is an agent.
Trigger: Use on a scheduled cadence across the cohort — weekly or at key milestones — to surface at-risk learners before disengagement becomes dropout.
Autonomy: Acts autonomously — runs end-to-end without a human in each loop.
Recognise the problem?
The primitives are the commodity part. The fastest next step is a conversation about composing them into something that works for you.
Start a conversation