Connect SmartTask and DataRobot to Build Intelligent Automations
Enable Integrations or automations with these events of SmartTask and DataRobot
Enable Integrations or automations with these events of SmartTask and DataRobot
Triggers
New Contact
Triggers when a new contact is added to the organization.
New Task
Triggers when a new task is added to the project.
Task Completion
Triggers when a task is marked completed.
Task Comment Added
Triggers when a comment is added on task .
Actions
List Organizations
Retrieve all the list of organizatons
Create Task
Creates a new task
List User
Retrieve the list of users
List Project
Retrieve list of all projects
Add Comment to Task
Adds a new comment to task
Create Contact
Creates a new contact
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Frequently Asked Questions
To start, connect both your SmartTask and DataRobot accounts to viaSocket. Once connected, you can set up a workflow where an event in SmartTask triggers actions in DataRobot (or vice versa).
Absolutely. You can customize how SmartTask data is recorded in DataRobot. This includes choosing which data fields go into which fields of DataRobot, setting up custom formats, and filtering out unwanted information.
The data sync between SmartTask and DataRobot 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 SmartTask and DataRobot. 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 SmartTask
SmartTask is an online work management tool helping teams streamline their communication and workflows.
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About DataRobot
DataRobot is a leading AI platform that enables organizations to harness the power of machine learning and artificial intelligence to drive business insights and decision-making. It offers automated machine learning capabilities, allowing users to build, deploy, and manage AI models efficiently.
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