Connect Gretel AI and Breezy HR to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Gretel AI
Choose an Action
Automatically do this!
Create candidate
Ready to use Gretel AI and Breezy HR automations
Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Active Position
Trigger when a position in active.
New Candidate
Trigger when a new candidate 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 Breezy HR accounts to viaSocket. Once connected, you can set up a workflow where an event in Gretel AI triggers actions in Breezy HR (or vice versa).
Absolutely. You can customize how Gretel AI data is recorded in Breezy HR. This includes choosing which data fields go into which fields of Breezy HR, setting up custom formats, and filtering out unwanted information.
The data sync between Gretel AI and Breezy HR 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 Breezy HR. 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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