Connect Thankster and Nyckel to Build Intelligent Automations
Enable Integrations or automations with these events of Thankster and Nyckel
Enable Integrations or automations with these events of Thankster and Nyckel
Actions
Find or Create User
Find or Create User By Email
Create Card Project
Creates a New Card
Apply Image
Apply Your Image in your Template
Order Project
Order Your Project
Send Card
Create and send a Thankster card.
Import to Classifier
Import data to your Nyckel classifier
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Frequently Asked Questions
To start, connect both your Thankster and Nyckel accounts to viaSocket. Once connected, you can set up a workflow where an event in Thankster triggers actions in Nyckel (or vice versa).
Absolutely. You can customize how Thankster data is recorded in Nyckel. This includes choosing which data fields go into which fields of Nyckel, setting up custom formats, and filtering out unwanted information.
The data sync between Thankster and Nyckel 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 Thankster and Nyckel. 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 Thankster
Thankster is an online platform that allows users to create and send personalized thank you cards and notes. It offers a variety of templates and customization options to help users express gratitude in a meaningful way. The service is ideal for both personal and business use, making it easy to maintain relationships and show appreciation.
Learn MoreAbout Nyckel
Nyckel is a platform that provides machine learning as a service, enabling users to easily integrate AI capabilities into their applications without needing extensive knowledge in data science or machine learning. It offers tools for creating, training, and deploying machine learning models with ease.
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