Connect Narrato and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
New Task
Update Task
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Narrato and Neo4j
Enable Integrations or automations with these events of Narrato and Neo4j
Triggers
New Task
Triggers when a new task is created inside a project.
Update Task
Triggers when task is updated.
Actions
Get all Project
Get details of all Projects in a Workspace
Get all Workspaces
Get details all workspaces associated with a user.
Find Task
Find a task inside the workspace and/or project to update the details optionally , create a task if not found.
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Frequently Asked Questions
To start, connect both your Narrato and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Narrato triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Narrato data is recorded in Neo4j. This includes choosing which data fields go into which fields of Neo4j, setting up custom formats, and filtering out unwanted information.
The data sync between Narrato and Neo4j 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 Narrato and Neo4j. 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 Narrato
Narrato is a comprehensive content creation and collaboration platform designed to streamline the content production process. It offers tools for content planning, writing, editing, and team collaboration, making it ideal for content marketers, writers, and editors.
Learn MoreAbout Neo4j
Neo4j is a leading graph database platform that enables organizations to unlock the value of connections, influences, and relationships in data. It is designed to handle highly connected data and is used for a variety of applications such as fraud detection, real-time recommendations, and network management.
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