Connect Elai and kazm to Build Intelligent Automations
Enable Integrations or automations with these events of Elai and kazm
Enable Integrations or automations with these events of Elai and kazm
Triggers
New Video Created
Triggers when new video is created in Elai Account.
Video Ready
Triggers when any video change it's status to "ready".
Video Error
Triggered when any video has a validation or a rendering error
Actions
Create a Video
create a new video.
Delete a Video
Deletes a video from Elai account.
Update a Video
Update a Video in the Elai account.
Render a Video
Re-render an existing video or fix previously failed video renders.
Copy/Transform Video
Duplicate videos or templates, and convert videos into templates or templates into videos.
Create a Stream
Creates a new Elai video stream using the selected avatar, voice provider, and voice ID.
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Frequently Asked Questions
To start, connect both your Elai and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in Elai triggers actions in kazm (or vice versa).
Absolutely. You can customize how Elai data is recorded in kazm. This includes choosing which data fields go into which fields of kazm, setting up custom formats, and filtering out unwanted information.
The data sync between Elai and kazm 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 Elai and kazm. 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 Elai
Elai.io is a leading text-to-video platform that allows anyone to build customized AI videos with a presenter using only text. A few moments is all it takes to generate a video with 69 languages available for translation.
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About kazm
Kazm is the data-driven CRM for Web3. We plug into every community touchpoint to create unified customer profiles, then apply machine learning and other methods to label, segment, and help personalize experiences for users.
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