Connect Deputy and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
New Employee
New Department
New Location
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Deputy and Neo4j
Enable Integrations or automations with these events of Deputy and Neo4j
Triggers
New Employee
Trigger when there is a new employee in created.
New Department
Trigger when a new department created.
New Location
Trigger when new location in created.
Actions
Get Company
Get Company details
Add an employee
Create a new staff member.
Add a location
Create a new location.
Get timesheets
View a timesheet
Create a Department
create a new department
Start an employees timesheet
Start a shift for your staff.
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Frequently Asked Questions
To start, connect both your Deputy and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Deputy triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Deputy 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 Deputy 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 Deputy 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 Deputy
Deputy is a comprehensive workforce management solution that simplifies scheduling, timesheets, tasking, and communication for businesses. It helps streamline operations and improve productivity by automating administrative tasks.
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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