Connect PayHere and Labelf to Build Intelligent Automations
Enable Integrations or automations with these events of PayHere and Labelf
Enable Integrations or automations with these events of PayHere and Labelf
Triggers
Payment Received
Triggers when a payment is received.
Subscription Cancelled
Triggers when a user has cancelled their subscription, or Stripe has marked it as cancelled due to payment failures.
Actions
Create a Plan
Creates a new payment plan
Update Current Company
Update the company information for currently authenticated user.
Issue a refund
Issue a refund a customer the amount specified, can be a partial refund.
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Frequently Asked Questions
To start, connect both your PayHere and Labelf accounts to viaSocket. Once connected, you can set up a workflow where an event in PayHere triggers actions in Labelf (or vice versa).
Absolutely. You can customize how PayHere 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 PayHere 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 PayHere 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 PayHere
PayHere is a comprehensive online payment gateway service that facilitates seamless and secure transactions for businesses and individuals in Sri Lanka. It supports multiple payment methods, including credit cards, mobile payments, and bank transfers, making it easier for users to manage their financial transactions online.
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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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