Connect TaxJar and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for TaxJar
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of TaxJar and Neo4j
Enable Integrations or automations with these events of TaxJar and Neo4j
Actions
Create an Order Transaction
Creates a new order transaction in TaxJar.
Create a Customer
Creates a new customer in TaxJar.
List Categories
Gets the latest product categories and corresponding tax codes.
List Customers
Lists existing customers created.
List Nexus Regions
Lists existing nexus regions for a TaxJar account, sorted alphabetically.
Create a Refund Transaction
Creates a new refund transaction in TaxJar.
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Frequently Asked Questions
To start, connect both your TaxJar and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in TaxJar triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how TaxJar 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 TaxJar 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 TaxJar 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 TaxJar
TaxJar’s award-winning solution makes it easy to automate sales tax management, reporting and filing. We obsessively leverage technology and exceptional customer service to help you focus on what matters most — growing your business.
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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