Connect Altoviz and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Altoviz
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Altoviz and Neo4j
Enable Integrations or automations with these events of Altoviz and Neo4j
Actions
Find a Sales Invoice
Find a sales invoice by internal ID. Optionally creates a sales invoice if none are found
Find Settings
Find an application settings
Find a Product
Find a product by its number. Optionally create a product if none is found
Find a Customer
Finds a customer by email-ID. Optionally creates a new customer if none are found
Find a Contact
Find a contact by Email.Optionally create a contact if none are found
Create a Contact
Creates a new contact
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Frequently Asked Questions
To start, connect both your Altoviz and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Altoviz triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Altoviz 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 Altoviz 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 Altoviz 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 Altoviz
Altoviz is a cloud-based invoicing and accounting platform** for small businesses, starting with a web application. It aims to empower entrepreneurs with an appealing and powerful platform.
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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