Connect Insighto.ai and Microsoft Azure Functions to Build Intelligent Automations
Choose a Trigger
When this happens...
New Contact
Choose an Action
Automatically do this!
- Request a new Action for Microsoft Azure Functions
Enable Integrations or automations with these events of Insighto.ai and Microsoft Azure Functions
Enable Integrations or automations with these events of Insighto.ai and Microsoft Azure Functions
Triggers
New Contact
Triggers when a new contact is created.
Actions
Create Contact
Creates a Contact in the system.
Add Text Blob Into Data Source
Adds a text blob into an existing Data Source.
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Frequently Asked Questions
To start, connect both your Insighto.ai and Microsoft Azure Functions accounts to viaSocket. Once connected, you can set up a workflow where an event in Insighto.ai triggers actions in Microsoft Azure Functions (or vice versa).
Absolutely. You can customize how Insighto.ai 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 Insighto.ai 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 Insighto.ai 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 Insighto.ai
Insighto.ai is a LLM-powered platform to create AI agents & automate business workflows
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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