The LearningUnify Intelligence Platform
A vendor-neutral layer that extracts, normalizes, reconciles and preserves learning records from every system you run, then makes them usable for reporting, audits, integrations and AI workflows.
Connect anything that holds learning data
Connectors are built around how your systems actually expose data, not around a single preferred API.
Sources
LMS, HRIS, SIS, content libraries, assessment engines and business systems such as CRM, finance and ticketing.
Methods
File exports, REST and GraphQL APIs, direct database connections, xAPI statement streams, SFTP drops and cloud storage buckets.
Learn more →Legacy and archive
Historical exports from decommissioned platforms, spreadsheets and PDF transcripts brought into the same model.
What the platform does with a record
Normalization
Maps every source field to a common learning data model while keeping the raw values alongside, so nothing is silently rewritten.
Learn more →Source lineage
Each record carries where it came from, when it was captured and every transformation applied to it.
Learn more →Identity reconciliation
Merges the same person across LMS usernames, HR employee IDs, student numbers and email changes, with a reviewable match log.
Learn more →Data-quality surfacing
Duplicates, missing completions, conflicting dates and orphaned enrollments are flagged with the evidence, not just counted.
Learn more →Outputs your teams can use today
Once records are normalized and governed, the same store serves every downstream need.
- Dashboards and scheduled reports
- BI exports to Power BI, Tableau, Snowflake and warehouses
- Audit pulls with evidence packs
- Integrations to HRIS, compliance and skills tools
- Controlled data movement between platforms
- Skills analysis across course and assessment history
- Context for AI and agent workflows
| Capability | Example |
|---|---|
| Audit pull | Everyone who completed a required course version in a given quarter, with source references |
| Migration validation | Record-by-record comparison of the old LMS and the new one before cut-over |
| Content audit | Courses with zero enrollments in 24 months that still carry licence costs |
| Skills analysis | Evidence of a skill drawn from assessments in three different systems |
Governance built in
Every dataset in the platform carries an owner, a permission model, a lineage record and a privacy classification. That inventory is what turns a pile of exports into something a BI team or an AI project can rely on.
Ownership
Named owners for every source and dataset.
Permissions
Role-based access aligned to your HR structure.
Lineage
Full trace from output back to source.
Retention
Policies for how long each class of record is kept.
See the platform on your own data
Bring a sample export from one of your systems and we will walk through how it is connected, normalized and preserved.