Connect Sulekha and Nyckel to Build Intelligent Automations
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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Leads
Triggers when the New Lead is captured.
Do thisActions
Action is the task that follows automatically within your Sulekha 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 Sulekha and Nyckel accounts to viaSocket. Once connected, you can set up a workflow where an event in Sulekha triggers actions in Nyckel (or vice versa).
Absolutely. You can customize how Sulekha 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 Sulekha 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 Sulekha 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 Sulekha
Sulekha is a comprehensive online platform connecting users with local service providers across various categories, including home services, education, and events. It facilitates easy access to trusted professionals and businesses, enhancing convenience and efficiency for users seeking specific services.
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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