Connect Agendor and Labelf to Build Intelligent Automations
Enable Integrations or automations with these events of Agendor and Labelf
Enable Integrations or automations with these events of Agendor and Labelf
Triggers
New Activity
Triggers when new activity created.
Deal Won
Check whether the deal status has been updated to **Won**.
Update Deal
Triggers when deal is updated.
Update Organization
Check if an organization has been updated.
Update Person
Triggers when person is updated.
New Deal
Triggers when new deal is created.
Actions
Create Task for a Deal
Create a new task related to a deal
Create Task for an Organization
Create a new task related to an organization
Create Task for a Person
Create a new task related to a person.
Update a Deal
Update a deal by its id
Get a Deal
Get details of a deal by its id
Create Deal for an Organization
Create a new deal for an organization by org id.
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Frequently Asked Questions
To start, connect both your Agendor and Labelf accounts to viaSocket. Once connected, you can set up a workflow where an event in Agendor triggers actions in Labelf (or vice versa).
Absolutely. You can customize how Agendor data is recorded in Labelf. This includes choosing which data fields go into which fields of Labelf, setting up custom formats, and filtering out unwanted information.
The data sync between Agendor and Labelf 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 Agendor and Labelf. 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 Agendor
Customer relationship management platform where user can manage organizations, people, task and deals.
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About Labelf
Labelf is an advanced AI-driven platform designed to streamline and enhance the process of labeling and annotating data. It leverages cutting-edge machine learning algorithms to provide accurate and efficient data labeling solutions, making it an essential tool for data scientists, machine learning engineers, and AI researchers.
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