Connect Pumble and V7 Go to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Pumble
Choose an Action
Automatically do this!
Create Project
Create a New Session
Delete Project
Update Project
Create an export
Delete an Export
Enable Integrations or automations with these events of Pumble and V7 Go
Enable Integrations or automations with these events of Pumble and V7 Go
Actions
Create a Channel
Create a new Pumble channel (public or private) with the specified name and optional description.
Send Channel Message
Send a message to a specified Pumble channel, optionally as a bot.
Send Private Channel Message
Send the provided text message to a selected private channel in Pumble.
Find Channel
Locate a Pumble channel by ID or name and return its details.
Find a User
Retrieve a Pumble user by email, name, or user ID.
Create Project
Creates a new project.
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Frequently Asked Questions
To start, connect both your Pumble and V7 Go accounts to viaSocket. Once connected, you can set up a workflow where an event in Pumble triggers actions in V7 Go (or vice versa).
Absolutely. You can customize how Pumble data is recorded in V7 Go. This includes choosing which data fields go into which fields of V7 Go, setting up custom formats, and filtering out unwanted information.
The data sync between Pumble and V7 Go 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 Pumble and V7 Go. 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 Pumble
Pumble is team messaging and video conferencing software for seamless communication and collaboration.
Learn MoreAbout V7 Go
V7 Go is a cutting-edge platform designed for AI-driven image and video annotation, streamlining the process of training machine learning models. It offers advanced tools for data labeling, management, and collaboration, making it an essential resource for developers and data scientists working on computer vision projects.
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