Akashic for education · Institutions & national programmes
Every learner. One connected journey.
Akashic already runs inside India’s national learning platform, connecting billions of learning interactions into decision-ready insight. The same foundation connects your campus: one governed journey from enrolment to placement.
Learner signal
Attendance · scores · fees
Journey graph
Enrolment · course · placement
Institution record
Cohort · programme · outcome
At-risk pattern · one learner
Flagged a term early · counsellor ready
Signals
3 of 3
Flagged
Wk 3
Window
1 term
Systems joined
You can count enrolments. You can’t see journeys.
What each system saw
Just noise.
Three systems · three unread signals
Each signal alone looks like a bad week. No system holds the person, so no system sees them add up.
What they added up to
Term end
Drop-out · discovered as paperwork
Together they were a drop-out announcing itself a term in advance. Nobody saw them together, so the intervention came after the exit, when it was already a report.
The gap between the signals and the person is where the drop-out hides.
Signal
Week 2
Signal
Week 3
Signal
Week 4
What the journey is already saying
RESOLVE
One learner, every system
Admissions, LMS, assessment, attendance, and fees resolve into one governed record.
PATTERN
At-risk combination matched
The three signals together match a known drop-out shape this cohort has shown before.
ACT
Counsellor reaches out
A conversation in week four, while there is still a term left to change the outcome.
1
The learner fragments across systems
Admissions, the LMS, assessment, hostels, and placement each hold a slice of the student. No one system holds the person.
2
Signals arrive after the outcome
Reports are compiled at term end, when the drop-out has already happened. The data that predicted it existed all along, in systems that never met.
3
Outcomes disconnect from teaching
Placement results, learning outcomes, and course design live in separate worlds. What worked, and for whom, stays anecdotal.
None of these are people problems. All of them are architecture problems.
No drop-out is sudden. Someone just has to see it coming.
Scroll through your own campus: the players you already have, and what changes when their data lands on one governed record.
- 01
The players
Every office holds a slice of the learner.
Admissions, classrooms, assessment, hostel, placement: five systems, five versions of the same student.
- 02
Signals stream
The journey starts writing itself.
Attendance, scores and fee events land on one governed record as they happen, all term long.
- 03
One learner forms
Rows become a journey.
Master data resolves every system's entries into one record per learner, visible role by role.
- 04
Someone sees it coming
A conversation in week four.
The at-risk pattern is flagged with a term to spare, and the counsellor reaches out before any exit paperwork exists.
One journey, from first enrolment to first job.
Akashic unifies every system that touches a learner into one governed record, flags risk while there's still a term left to act, and answers the questions institutions actually ask, with the evidence attached.
01 / Unify
Every system, one learner
Data Pipelines connect the SIS, LMS, assessment, attendance, and placement systems. Master Data resolves them into one governed record per learner.
02 / Govern
A record that protects the student
Access rules and masking execute at the platform layer, so counsellors, faculty, and administrators each see exactly what their role permits, with every access stamped.
03 / Predict
Risk flagged a term early
Models trained on your own cohorts recognise the combination of signals that precedes a drop-out or a failing outcome, while there is still time to intervene.
04 / Act
Questions answered with evidence
Which cohorts are struggling, which courses lead to placements, which interventions worked: asked in plain language, answered with the source data attached.
Every module runs on the same governed foundation · every answer arrives with its lineage
What changes on campus.
Same faculty. Same systems. Learners seen as journeys instead of rows in five databases.
BeforeDrop-outs discovered in term-end reports
AfterAt-risk learners flagged a term in advance
BeforeThe student assembled from five systems by hand
AfterOne governed record per learner
BeforeCourse effectiveness argued from anecdote
AfterOutcomes traced from classroom to placement
BeforeCompliance reporting as an annual scramble
AfterRegulator-ready reports from governed data
Let's talk about your learners.
The intelligence layer inside India's national learning platform is the same foundation we deploy for institutions. We'd like to show you what one connected learner journey looks like for your campus.