Connect NativeBridge and mtalkz to Build Intelligent Automations
Choose a Trigger
When this happens...
New Upload Application
Choose an Action
Automatically do this!
- Request a new Action for mtalkz
Enable Integrations or automations with these events of NativeBridge and mtalkz
Enable Integrations or automations with these events of NativeBridge and mtalkz
Triggers
New Upload Application
Trigger When new Application Upload
Actions
List all Devices
List all Devices
List User Uploaded Applications
List User Uploaded Applications
Get all Session Details by ID
Get all Session Details by ID
Delete a Session
Delete a Session
Create a Session
Create a Session in NativeBridge.
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Frequently Asked Questions
To start, connect both your NativeBridge and mtalkz accounts to viaSocket. Once connected, you can set up a workflow where an event in NativeBridge triggers actions in mtalkz (or vice versa).
Absolutely. You can customize how NativeBridge data is recorded in mtalkz. This includes choosing which data fields go into which fields of mtalkz, setting up custom formats, and filtering out unwanted information.
The data sync between NativeBridge and mtalkz 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 NativeBridge and mtalkz. 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 NativeBridge
NativeBridge is a platform designed to facilitate seamless integration and communication between various software applications and services. It provides tools and solutions to connect different systems, enabling efficient data exchange and workflow automation.
Learn MoreAbout mtalkz
Mtalkz is a cloud-based communication platform that lets you transform your customer sms campaigns with predictive analysis using AI/ML.
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