Connect Picsart and kazm to Build Intelligent Automations
Enable Integrations or automations with these events of Picsart and kazm
Enable Integrations or automations with these events of Picsart and kazm
Actions
Change Image Background
Changes the background of an image.
Upscale Image
The Upscale module uses AI to boost resolution and increase the quality of your images.
Remove Image Background
Automatically remove the image backdrop and cut out the main subject with a clean, transparent background.
Ultra Upscale Image
Ultra Upscale uses predictive AI to boost resolution, upscale images with noise suppression, and enhance low-res photos, stickers, and geometric shapes.
Ultra Enhance Image
Ultra Enhance is an advanced upscaling technique powered by a generative AI model that boosts resolution and adds high-frequency detail.
Rotate Image by Angle
Rotates an image by a specified angle.
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Frequently Asked Questions
To start, connect both your Picsart and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in Picsart triggers actions in kazm (or vice versa).
Absolutely. You can customize how Picsart 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 Picsart 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 Picsart 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 Picsart
Picsart offers creative APIs to boost artistic expression on multiple platforms. Our tools unleash creativity, empowering users to experiment with imagination.
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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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