Connect Mailparser and Nyckel to Build Intelligent Automations
Ready to use Mailparser and Nyckel automations
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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Email Parsed One Request Per Row
Triggers when a new email is parsed in an inbox, and create one request for each row if the result contains a tabular result.
New Email Parsed One Request Per Email
Triggers when a new email is parsed in an inbox, and create one request for one email.
Do thisActions
Action is the task that follows automatically within your Mailparser integrations.
Import to Classifier
Import data to your Nyckel classifier
Classify
Classify image or text data
Center Detect
Detect Objects center in images
Train Classifier
Train your Nyckel classifier by adding more data
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Frequently Asked Questions
To start, connect both your Mailparser and Nyckel accounts to viaSocket. Once connected, you can set up a workflow where an event in Mailparser triggers actions in Nyckel (or vice versa).
Absolutely. You can customize how Mailparser 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 Mailparser 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 Mailparser 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 Mailparser
Send emails to Mailparser, get structured data in return. Leads, Contact Forms, eCommerce, Shipping Notes, Attachments, Customer Info & more.
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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