Connect PixelBin.io and kazm to Build Intelligent Automations
Enable Integrations or automations with these events of PixelBin.io and kazm
Enable Integrations or automations with these events of PixelBin.io and kazm
Triggers
Create Folder
Creates a new folder in your PixelBin account to organize images and sends the configured 'create folder' webhook to viaSocket.
Delete File
Receives PixelBin 'file delete' webhook events and triggers the corresponding viaSocket workflow.
File Created
Sends PixelBin's file-create webhook payload to viaSocket when a new file is created.
Actions
Upload File
This action upload an image to PixelBin.io and return url.
Upscale Image
Enhance and Upscale images with superior quality.
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Frequently Asked Questions
To start, connect both your PixelBin.io and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in PixelBin.io triggers actions in kazm (or vice versa).
Absolutely. You can customize how PixelBin.io 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 PixelBin.io 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 PixelBin.io 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 PixelBin.io
PixelBin.io is a platform that provides advanced image processing and optimization solutions. It allows users to manage, transform, and deliver images efficiently, ensuring high-quality visuals with reduced load times. The service is ideal for developers and businesses looking to enhance their digital content delivery.
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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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