Connect Supermemory and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of Supermemory and Neo4j
Enable Integrations or automations with these events of Supermemory and Neo4j
Actions
Search Memory
Search Supermemory for documents matching the query and return relevant memory results.
List All Documents
Retrieve saved memories with optional filters for memory ID, tags, metadata, and sorting order.
Create Memory
Create a Memory in supermemory.
Upload Document
Upload a document file or text to Supermemory to be processed.
Delete Document by ID
Permanently delete a Supermemory document specified by its document ID.
Update Document
update the document bu providing document ID.
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Frequently Asked Questions
To start, connect both your Supermemory and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Supermemory triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Supermemory 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 Supermemory 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 Supermemory 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 Supermemory
Supermemory is an advanced AI tool designed to enhance memory retention and cognitive skills. It leverages cutting-edge artificial intelligence to provide personalized learning experiences, helping users improve their memory and learning 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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