Company
We build for the gap between a job someone has and the job they are growing into.
Eduserge started from a simple observation: organizations spend heavily on training and still hire from outside for roles their own people could have grown into. The training was real. It just was not aimed at the gap.
Why we started
Generic training does not close the gaps that matter.
Most corporate learning is organized around a catalog. Courses are bought, assigned by department, and tracked by completion. The dashboard looks healthy. Yet when a lead role opens, nobody inside is clearly ready, and the reasons are usually specific: one missing skill in negotiation, one in coaching, one in owning a budget.
Those specific gaps are knowable. They sit in the difference between two role definitions and in the assessment data most organizations already collect. What was missing was a way to see them per person, build a path aimed only at them, and count progress in skills closed rather than hours spent.
That is what Eduserge does. We map the gap, build the path from the content you already own, and give managers a view of readiness they can trust, because every score shows its evidence and none of them makes a decision on anyone's behalf.
Principles
Three rules we build by.
Train the gap, not the catalog.
A path should contain only what a person needs for the role in front of them. Anything else is time taken from work and from the skills that matter.
Readiness is a signal, not a verdict.
A score helps a manager ask better questions. It never replaces the conversation, the judgement or the accountability that comes with a people decision.
Built for managers, not just L&D reporting.
If the person who runs the 1:1 does not find it useful every week, the dashboard is decoration. We design for that manager first.
What we build
- Skill gap maps grounded in your own role definitions
- Training paths assembled from content you already own
- Readiness scores that show their evidence
- Views managers open before every 1:1
What we will not build
- Automated promotion or rejection decisions
- Rankings of employees against each other
- Scores inferred from time spent in training
- Models trained on one customer's data for another