Connect Teachfloor and AI/ML API to Build Intelligent Automations
Choose a Trigger
When this happens...
Course Updated
Module Is Created
Element Is Created
Choose an Action
Automatically do this!
Create Chat Completion
Ready to use Teachfloor and AI/ML API automations
Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
Course Updated
Runs when course is updated
Module Is Created
Runs when module is created
Element Is Created
Runs when element is created
Do thisActions
Action is the task that follows automatically within your Teachfloor integrations.
Invite User By Email
Send invite to join org/course
Create Chat Completion
Initiates a conversation with the AI model, providing prompts and generating responses based on the chat messages.
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Frequently Asked Questions
To start, connect both your Teachfloor and AI/ML API accounts to viaSocket. Once connected, you can set up a workflow where an event in Teachfloor triggers actions in AI/ML API (or vice versa).
Absolutely. You can customize how Teachfloor data is recorded in AI/ML API. This includes choosing which data fields go into which fields of AI/ML API, setting up custom formats, and filtering out unwanted information.
The data sync between Teachfloor and AI/ML API 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 Teachfloor and AI/ML API. 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 Teachfloor
Teachfloor is an online cohort-based courses platform that allows any instructors to set up in just one-click their own online live academy
Learn MoreAbout AI/ML API
AI/ML API provides advanced artificial intelligence and machine learning capabilities to developers and businesses, enabling them to integrate intelligent features into their applications. With a wide range of AI models and tools, users can enhance their software with capabilities such as natural language processing, image recognition, predictive analytics, and more.
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