Connect Clockify and Nyckel to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Clockify
Choose an Action
Automatically do this!
Import to Classifier
Classify
Center Detect
Train Classifier
Enable Integrations or automations with these events of Clockify and Nyckel
Enable Integrations or automations with these events of Clockify and Nyckel
Actions
Find Project
Find a Project in a workspace.
Update a Client
Update your Client here
Delete a Client
Delete a Client
Create Client
Create a new client
Find Client
Find a Client in Workspace.
Find Task
Find Task by Name on a specified project and workspace.
Know More About Clockify and Nyckel Integrations
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Frequently Asked Questions
To start, connect both your Clockify and Nyckel accounts to viaSocket. Once connected, you can set up a workflow where an event in Clockify triggers actions in Nyckel (or vice versa).
Absolutely. You can customize how Clockify data is recorded in Nyckel. This includes choosing which data fields go into which fields of Nyckel, setting up custom formats, and filtering out unwanted information.
The data sync between Clockify and Nyckel 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 Clockify and Nyckel. 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 Clockify
Clockify, a time tracking and timesheet application, enables project-based work hour tracking for unlimited users at no cost.
Learn MoreAbout Nyckel
Nyckel is a platform that provides machine learning as a service, enabling users to easily integrate AI capabilities into their applications without needing extensive knowledge in data science or machine learning. It offers tools for creating, training, and deploying machine learning models with ease.
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