Alumni intelligence

Where your graduates went, not just where they were placed.

Career timelines for 7,645 alumni across 982 institutions, assembled by rules rather than judgement, so every row in an accreditation file traces back to the record it came from.

7,645 alumni982 institutionsDeterministic extraction
How a career is readDeterministic
01ProfileSix dimensions read: experience, education, certifications, skills, publications, volunteering
02TimelineAssembled by rules, so the same profile gives the same answer every time
03EmployersResolved against 71,785 company records, not free text
04EvidenceDestination, velocity and post-graduation gaps, per cohort

Missing periods are recorded as gaps, not smoothed over

Six dimensions, one timeline

Six dimensions, each traceable to a field.

It takes what is stated, records where each statement came from, and marks what is missing.

DimensionWhat it is resolved against
  • Experience

    Employers, titles and dates, resolved against the same 71,785 company records the job corpus uses, so an alumni employer and a hiring employer are the same object.

  • Education

    Programme, institution and period, which is what lets a career be attributed to the right cohort rather than to the institution as a whole.

  • Certifications

    Post-graduation credentials, often the clearest signal that a programme left a gap the graduate had to close themselves.

  • Skills

    Self-declared skills, resolved into the governed taxonomy so they can be compared against what employers actually ask for.

  • Publications

    Relevant for research programmes and for accreditation files that have to evidence scholarly output beyond teaching.

  • Volunteer work

    Read because it frequently carries the leadership and stakeholder evidence that a job title does not.

Rules, not judgement.

Extraction is deterministic: the same profile produces the same timeline on every run, and each entry points back at the field it came from. That is a deliberate constraint. A model that infers a plausible career history produces a better-looking dataset and a worse piece of evidence.

What an assessor will accept

Four things a dean can put in front of an assessor.

  1. 01

    Destination

    Where a cohort ended up

    Employers and roles by programme and by graduating year, resolved to archetypes rather than to job titles, so two cohorts can actually be compared.

  2. 02

    Velocity

    How fast they moved

    Time to first role, and movement between roles afterwards. Two programmes with identical placement percentages rarely have identical velocity.

  3. 03

    Gap evidence

    What they had to learn afterwards

    Certifications and skills acquired after graduation, held against the syllabus they were taught.

  4. 04

    Accreditation file

    Sourced, not assembled by hand

    The employability numbers in a NAAC, NIRF or NBA submission, each traceable to the record it came from.

Privacy is a control, not a promise

Individual graduates are people, not data points.

  • Masking is a control, not a request

    An administrator can mask compensation and named-graduate detail so a dashboard can be opened in a board meeting without exposing an individual.

  • Gaps stay visible

    Missing periods and unresolved employers are flagged in the output. A clean alumni dataset is usually a hidden one.

  • Cohort by cohort

    MBA/PGDM is the validated cohort today. Others are added once extraction has been tested against them, not before.

Explore Nexus

Five capabilities, one evidence base.

Each one is a different question about the same corpus. They share a vocabulary, so a finding in one holds up inside another.

Before you ask

What registrars and IQAC teams ask.

Where does alumni data come from?

Public professional profiles, plus whatever the institution already holds and chooses to bring. Nothing is purchased from a data broker and nothing is inferred about an individual beyond what their own profile states.

What does "deterministic" mean here, and why does it matter?

It means the timeline is assembled by rules, not by a language model's judgement. The same profile produces the same timeline every time, and every entry points back to the profile field it came from. For an accreditation file that reproducibility is the whole value - an assessor can ask where one row came from and get an answer.

What happens when a profile is incomplete?

The gap is recorded as a gap. The analyser flags missing periods and unresolved employers rather than smoothing them over, and those flags stay visible in the output. An alumni dataset with no recorded gaps has been cleaned until it stopped being evidence.

Is this compliant with how we are allowed to handle graduate data?

An administrator control masks compensation and named-graduate detail, so a screen can be opened in an open meeting or a board session without exposing an individual. Institutions with specific residency requirements should raise them before procurement - on-premise deployment exists for exactly this reason.

Which cohorts have been validated so far?

MBA and PGDM is the first validation cohort - the profile shapes are consistent enough to test extraction rules against, and the career paths are varied enough to break them. The analyser is at v0.2.0 and cohorts are added as extraction is validated against them, rather than switched on everywhere and corrected later.

Bring one cohort. We will show you where it actually went.

Forty-five minutes, one programme, five years of graduate careers on screen.

We reply within 48 hours. +91 88796 54341