Connect Pyrus and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Pyrus
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Pyrus and Neo4j
Enable Integrations or automations with these events of Pyrus and Neo4j
Actions
Create Simple Task
Creates a simple task with contacts
Get Forms
Get an existing form details by it's form id.
Create Task With Form
Creates a new task With an existing Form.
Delete Task
Delete task by task id.
Add Member
Add a new team member.
List Forms
Returns a description of all the forms in which the current user is a manager or a member.
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Frequently Asked Questions
To start, connect both your Pyrus and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Pyrus triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Pyrus 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 Pyrus 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 Pyrus 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 Pyrus
Pyrus is a collaborative work management platform designed to streamline workflows, automate routine tasks, and enhance team productivity. It offers features such as task management, approval workflows, and real-time collaboration to help businesses operate more efficiently.
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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