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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New conversation
Trigger when new conversation is created
New message
Trigger when new message is created
New contact
Trigger when new contact is created
Do thisActions
Action is the task that follows automatically within your Reamaze integrations.
Compute CLIP Similarity
Compute how closely an image matches a text prompt using Roboflow's CLIP model.
Create Classification Prediction
Generate class predictions for an image.
Run Instance Segmentation
Create instance segmentation predictions (masks and labels) for a given image.
Detect Objects in Image
Detect objects in an image and return their labels and bounding boxes.
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Frequently Asked Questions
To start, connect both your Reamaze and Roboflow accounts to viaSocket. Once connected, you can set up a workflow where an event in Reamaze triggers actions in Roboflow (or vice versa).
Absolutely. You can customize how Reamaze data is recorded in Roboflow. This includes choosing which data fields go into which fields of Roboflow, setting up custom formats, and filtering out unwanted information.
The data sync between Reamaze and Roboflow 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 Reamaze and Roboflow. 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 Reamaze
Reamaze is a web-based customer communication platform that integrates email, social media, and live chat functionalities to provide a comprehensive support solution for businesses.
Learn MoreAbout Roboflow
Roboflow is a leading platform for computer vision and AI model development, offering tools to streamline the process of building, training, and deploying machine learning models.
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