Student-level intelligence
The student is the unit of intelligence.
Not the class. Not the section. The individual learner.
Aggregate dashboards tell you classroom averages. A Student Intelligence Platform tells you which individual student needs which intervention — across attendance, performance, behaviour, concepts and engagement.
What it does
Four per-student capabilities.
Risk score per student
Multi-signal AI scoring updated weekly. Critical / At-Risk / Watch / Recovered tiers.
Performance trajectory
Slope over time across subjects, not just snapshots.
Concept strength mapping
Which topics the student is strong in, weak in, and what to practise next.
Career direction projection
Long-view: where the student's strengths point, with a recommended practice plan.
Why per-student matters
Aggregate metrics hide the students who need attention.
A class with a 78% average looks fine on a dashboard. Inside it: three students dropping silently from 80 to 55, one student stuck on basics, one quietly excelling without recognition. Aggregate dashboards miss all five stories.
Per-student intelligence is the difference between knowing the average and knowing the student. Edullent builds at this granularity by design — the home screen shows individual students, not classroom averages.
FAQs
Common questions.
A platform that builds and maintains a per-student intelligence profile — risk score, performance trajectory, concept strengths, behavioural signals — and uses it to drive interventions, communications and recommendations across the school.
An LMS delivers content. A Student Intelligence Platform watches what happens with the student and decides what to do next. They complement each other — many schools use an LMS for delivery and Edullent for intelligence.
No. The intelligence is built from data the school already produces — attendance, marks, behaviour notes, parent communication, fees. No new hardware, no sensors, no biometric overhead.
Continue exploring
Make the student the unit of intelligence.
A 25-minute walkthrough of per-student risk prediction, concept mapping and intervention workflows.