Connect LiveChat and Microsoft Azure Functions to Build Intelligent Automations
Choose a Trigger
When this happens...
New Chat
Finished Chat
Chat Changed
Choose an Action
Automatically do this!
- Request a new Action for Microsoft Azure Functions
Enable Integrations or automations with these events of LiveChat and Microsoft Azure Functions
Enable Integrations or automations with these events of LiveChat and Microsoft Azure Functions
Triggers
New Chat
Triggers when the chat is started.
Finished Chat
Triggers when the chat is ended.
Chat Changed
Triggers when the tag list for a chat was changed.
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Frequently Asked Questions
To start, connect both your LiveChat and Microsoft Azure Functions accounts to viaSocket. Once connected, you can set up a workflow where an event in LiveChat triggers actions in Microsoft Azure Functions (or vice versa).
Absolutely. You can customize how LiveChat data is recorded in Microsoft Azure Functions. This includes choosing which data fields go into which fields of Microsoft Azure Functions, setting up custom formats, and filtering out unwanted information.
The data sync between LiveChat and Microsoft Azure Functions 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 LiveChat and Microsoft Azure Functions. 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 LiveChat
LiveChat is the faster way to contact your customers. It is a web-based chat tool that lets you chat with your website visitors.
Learn MoreAbout Microsoft Azure Functions
Microsoft Azure Functions is a serverless computing service that enables developers to run event-driven code without having to explicitly provision or manage infrastructure. It allows for the execution of code in response to various triggers, such as HTTP requests, database changes, or message queue events, making it ideal for building scalable and efficient applications.
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