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You have three subsidiaries running the same ERP. Each one needs the same Salesforce integration - same fields, same logic, same schedule. Do you really need three separate sets of transfers?
This article covers how Tags in Rapidi let you parameterize transfers so the same configuration works across multiple companies, regions, or environments - without duplicating anything.
Watch the full 30-minute walkthrough below.
Tags are variables you define at the company or environment level that get injected into your transfers at runtime. Think of them as configuration parameters that let you write one transfer and run it in multiple contexts.
For example, if you integrate Salesforce with three Dynamics 365 Business Central companies, the transfer logic (which fields to map, what order to sync, how to handle errors) is identical. The only difference is which BC company the data flows to. Tags let you define that company as a variable.
Tags are most valuable when you have:
In MyRapidi, you define Tags as key-value pairs at the connection or schedule level. When a transfer runs, Rapidi resolves the Tag values and injects them into the appropriate fields - connection strings, filter conditions, default values, or any other configurable element.
This means you maintain one set of transfer definitions and one set of field mappings. The Tags handle the variation.
The setup process involves three steps:
The most common pattern is a hub-and-spoke setup: one Salesforce org connected to multiple ERP companies. Each company gets its own Tag set, but they all share the same transfers, mappings, and schedules.
This pattern scales well - adding a new company means creating a new Tag set and activating it, not rebuilding the entire integration.
COMPANY_CODE, BC_ENDPOINT) so they are self-documenting.Yes. Tags can be referenced in field mappings, default values, filter conditions, and connection settings.
There is no practical limit. Create as many as you need to parameterize your setup.
No. Tag resolution happens before the transfer runs and adds negligible overhead.
Andreea Arseni, Senior Data Integration Consultant
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