Connect Chatlayer and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
New Bot
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Chatlayer and Neo4j
Enable Integrations or automations with these events of Chatlayer and Neo4j
Triggers
New Bot
Triggered when a new bot is created.
Actions
Send Message
Sends a message to a user through Chatlayer.
Create Channel
Creates a Channel.
Delete Channel
Delete an existing channel.
Extract NLP Result
Extract results from the Chatlayer NLP models of your bots.
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Frequently Asked Questions
To start, connect both your Chatlayer and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Chatlayer triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Chatlayer 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 Chatlayer 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 Chatlayer 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 Chatlayer
Chatlayer is a powerful AI-driven platform designed to create, manage, and optimize chatbots for various communication needs. It enables businesses to automate customer interactions, enhance user engagement, and improve customer support through intelligent conversational agents.
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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