Connect GorillaDesk and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of GorillaDesk and Neo4j
Enable Integrations or automations with these events of GorillaDesk and Neo4j
Triggers
New Customer
Triggers when a new customer is created.
Updated Customer
Trigger when an existing customer is updated.
Actions
Add a Customer
Adds a new customer to GorillaDesk.
Add a Lead
Adds a new lead to GorillaDesk.
Add a Booking
Adds a new event inside GorillaDesk with the status pending booking on the schedule.
Get Company
Get Company for the account.
List Users
Get all users form GorillaDesk.
List Customer
Get all customer form GorillaDesk.
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Frequently Asked Questions
To start, connect both your GorillaDesk and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in GorillaDesk triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how GorillaDesk 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 GorillaDesk 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 GorillaDesk 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 GorillaDesk
GorillaDesk is a comprehensive field service management software designed to streamline operations for service-based businesses. It offers features such as scheduling, invoicing, customer management, and reporting to enhance productivity and efficiency.
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About 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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