The problem
The same learner appears as an LMS username, an HR employee ID, a student number, two email addresses and a name that changed after a marriage. Left alone, that is five people with fragments of history and no complete record of anything.
How matching works
- Deterministic rules first: shared identifiers, verified email, HR-linked keys
- Probabilistic matching second: name, date of birth, org unit and timing signals, each scored
- Confidence thresholds set with your team, with anything below auto-merge routed to review
- A reviewable match log recording every merge, split and rejection, and who decided it
Role and system changes
When someone moves department, changes name or is re-created in a new platform after a migration, the reconciled identity persists. Completions recorded under the old identifier remain attached to the person, with the mapping between identifiers preserved for audit.
Privacy by design
Reconciliation runs inside the governed layer under your permission model. Matching attributes are classified as personal data, access to them is logged, and they are retained only as long as the retention policy allows.
Ready to see your learning data in one place?
Tell us which systems you run and we will show how the platform connects, normalizes and preserves their records.