Every system's schema. One shared model
Salesforce, Marketo, the warehouse, and the ad platforms each name things their own way. Harmonization maps every field, value, and taxonomy to one canonical model your agents and models can reason over.
Data harmonization maps every field, value, and taxonomy from your CRM, marketing automation, warehouse, and ad platforms to one canonical model. Where Salesforce, Marketo, and the warehouse each name the same thing differently, RevSure harmonizes them on its context layer, so attribution, forecasting, and agents reason over one shared definition instead of reconciling schemas by hand.
Same field. Five different names
| Source | Field | Canonical |
|---|---|---|
| Salesforce | LeadSource | channel |
| Marketo | utm_source | channel |
| Google Ads | campaign_id | campaign |
| Warehouse | acct_stage | stage |
| HubSpot | lifecyclestage | stage |
Lead Source in one system is utm_source in another and Channel in a third. Stage names disagree, picklists drift, and currencies mix. No model can learn on data that does not speak one language.
- Field names that mean the same thing but never match
- Picklist and stage taxonomies that disagree across tools
- Mixed units, currencies, and date formats
- Free-text values where a controlled vocabulary should be
One model everything maps to
| Field | Type | Sources mapped |
|---|---|---|
| channel | enum | 6 |
| stage | enum | 4 |
| segment | enum | 3 |
| arr | currency | 5 |
RevSure resolves each source into a single canonical schema: accounts, people, opportunities, campaigns, and touches, with one taxonomy for stages, channels, and segments. Map once, and every new source inherits it.
- A canonical schema for the whole funnel
- One taxonomy for stages, channels, and segments
- Unit, currency, and date normalization on ingest
- New sources map to the model, not the other way around
Change the mapping. Keep the history
Mappings are versioned and owned, so a taxonomy change is auditable and reversible, and a new rep mislabeling a stage does not quietly corrupt a quarter of reporting.
- Versioned mappings with an owner and an audit trail
- Validation that catches drift before it reaches a model
- Reversible changes, so a bad mapping is one click back
- Consistent definitions across every report and agent
Mapping that holds up
Related capabilities
The Context Layer
The identity-resolved spine the whole platform runs on.
ExploreIdentity Resolution
Reconcile every system into one account agents act on.
ExploreData Hygiene & Maintenance
Continuous dedup, validation, and decay control.
ExploreFull Funnel Data Graph
Touch to revenue, connected in one graph.
ExploreQuestions, answered
What is data harmonization?
Data harmonization is the process of mapping different systems' fields, values, and taxonomies to one canonical model, so every tool describes the same entity the same way. It is the step that makes cross-system attribution and reporting trustworthy, because the numbers finally add up to one definition.
How is data harmonization different from data integration?
Integration moves data between systems. Harmonization makes that data agree once it arrives, reconciling naming, units, and taxonomies to a shared model. RevSure does both on the context layer: it ingests from 25+ sources and harmonizes them into one model agents can reason over.
Does harmonization change my source systems?
No. RevSure harmonizes into its own canonical model and leaves your systems of record intact. Resolved, harmonized values can be written back to your CRM and ad platforms when you want them there, but the mapping lives on the context layer.
One model. Every source speaks it
See your stack harmonized to one schema.