Connect Clientary and Labelf to Build Intelligent Automations
Enable Integrations or automations with these events of Clientary and Labelf
Enable Integrations or automations with these events of Clientary and Labelf
Triggers
New Expense
A new expense in Clientary.
New Project
Triggered when a new project is created in Clientary.
New Client
Triggered when a new client is created in Clientary.
New Estimate
Triggered when a new estimate is created in Clientary.
New Invoice
A new invoice is created in Clientary.
New Contracts
An individual Contracts within Clientary.
Actions
Create Client
Create a new client in Clientary.
Create Expense
Create a new expense in Clientary.
Create Task
Create a task inside Clientary.
Create Entry
Create A New Entry.
Create Invoice Payment
Create A New Invoice Payment.
Update Expense
Update an exsiting expense.
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Frequently Asked Questions
To start, connect both your Clientary and Labelf accounts to viaSocket. Once connected, you can set up a workflow where an event in Clientary triggers actions in Labelf (or vice versa).
Absolutely. You can customize how Clientary 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 Clientary 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 Clientary 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 Clientary
Online invoicing and time tracking for small businesses and freelancers. Clientary helps you get paid quicker and painlessly helps you manage your staff and projects.
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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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