Connect Payrexx and Scale to Build Intelligent Automations
Enable Integrations or automations with these events of Payrexx and Scale
Enable Integrations or automations with these events of Payrexx and Scale
Actions
Create a Design
Create a new Design.
Update a Design
Update a specific design by id.
Get Tasks
Retrieve all the tasks for given project.
Create Batch
Create a new batch in a project to group related tasks for processing.
Pause Batch
Pause processing of an in-progress Batch. Only unstarted tasks will be paused.
Resume Batch
Resume processing of a paused Batch. Previously paused tasks will be resumed.
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Frequently Asked Questions
To start, connect both your Payrexx and Scale accounts to viaSocket. Once connected, you can set up a workflow where an event in Payrexx triggers actions in Scale (or vice versa).
Absolutely. You can customize how Payrexx data is recorded in Scale. This includes choosing which data fields go into which fields of Scale, setting up custom formats, and filtering out unwanted information.
The data sync between Payrexx and Scale typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Payrexx and Scale. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Payrexx
Payrexx is a versatile payment processing platform designed to simplify online transactions for businesses of all sizes. It offers a user-friendly interface and a range of tools to manage payments, subscriptions, and donations efficiently. With Payrexx, businesses can easily integrate various payment methods, ensuring a seamless checkout experience for their customers.
Learn MoreAbout Scale
Scale provides advanced AI-driven solutions for data labeling and annotation, helping businesses streamline their machine learning workflows.
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