Connect Gretel AI and Recras to Build Intelligent Automations
Ready to use Gretel AI and Recras automations
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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Booking
Triggers when a new booking is created.
New Contact
Triggers when a new contact is created.
Invoice Sent
Triggers when an invoice is (marked as) sent.
New Start Moment
Triggers when a new start moment is created.
New Attachment
Triggers when a new attachment is created.
New Company
Triggers when a new company is created.
Do thisActions
Action is the task that follows automatically within your Gretel AI integrations.
Get a specific Project
Fetch a single project owned or belonged to by the current user by the project ID or project name.
Create project
Create a project. Project names must be globally unique and DNS name compliant.
List Project
List all projects the current user owns.
Update Project
Update information about a project.
Delete Project
Delete a project.
List Project Members
List all current/active members of a project.
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Frequently Asked Questions
To start, connect both your Gretel AI and Recras accounts to viaSocket. Once connected, you can set up a workflow where an event in Gretel AI triggers actions in Recras (or vice versa).
Absolutely. You can customize how Gretel AI data is recorded in Recras. This includes choosing which data fields go into which fields of Recras, setting up custom formats, and filtering out unwanted information.
The data sync between Gretel AI and Recras 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 Gretel AI and Recras. 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 Gretel AI
Gretel AI provides tools and APIs to generate synthetic data, ensuring privacy and security while enabling data sharing and collaboration. It is designed to help developers and data scientists create high-quality, privacy-preserving synthetic data for machine learning and analytics.
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