
When this happens...
Text Created
Media Created
Text Analyzed
Text Failed
Embedded Recorder Created
Media Analyzed
Embedded Recorder Deleted
Embedded Recorder Recording Received
Chat Status
New Folder Created
Folder Updated
New Magic Prompts Response
New Events Created
Events Updated
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When this happensTriggers
A trigger is an event that starts a workflow.
Triggers when a new text is created.
Triggers when media is created.
Triggers when an existing text is analyzed.
Triggers when text is failed.
Triggers when embedded recorder is created..
Triggers when media is analyzed.
Action is the task that follows automatically within your Speak AI integrations.
Run a Magic Prompt with your media data.
Creates a new note with the given text content and name.
create a new folder.
Creates a User.
Creates a Embed.
Schedule an Event.

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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your Speak AI and Signadot accounts to viaSocket. Once connected, you can set up a workflow where an event in Speak AI triggers actions in Signadot (or vice versa).
Absolutely. You can customize how Speak AI data is recorded in Signadot. This includes choosing which data fields go into which fields of Signadot, setting up custom formats, and filtering out unwanted information.
The data sync between Speak AI and Signadot 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 Speak AI and Signadot. 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.
Speak Ai is a tool to analyze audio and video to get insights extraction and transcriptions.
Learn MoreSignadot is a platform designed to streamline and enhance the process of testing and deploying microservices in a Kubernetes environment. It provides developers with the tools to create isolated environments for testing, ensuring that changes can be validated before being merged into the main codebase. This helps in reducing the risk of errors and improving the overall efficiency of the development process.
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