Connect CARTO and V7 Go to Build Intelligent Automations
Choose a Trigger
When this happens...
New Job
Choose an Action
Automatically do this!
Create Project
Create a New Session
Delete Project
Update Project
Create an export
Delete an Export
Ready to use CARTO and V7 Go automations
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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Job
Triggers when new job is created.
Do thisActions
Action is the task that follows automatically within your CARTO integrations.
Import Job
Import a job.
Create Project
Creates a new project.
Create a New Session
Create a new session
Delete Project
Delete a project.
Update Project
Update a project .
Create an export
Creates a new export
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Frequently Asked Questions
To start, connect both your CARTO and V7 Go accounts to viaSocket. Once connected, you can set up a workflow where an event in CARTO triggers actions in V7 Go (or vice versa).
Absolutely. You can customize how CARTO 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 CARTO 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 CARTO 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 CARTO
CARTO is a powerful platform for location intelligence and spatial data analysis. It enables users to visualize, analyze, and gain insights from geospatial data, making it an essential tool for businesses and organizations looking to leverage location-based data for decision-making and strategic planning.
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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