Connect VectorShift and Watershed LRS to Build Intelligent Automations
Enable Integrations or automations with these events of VectorShift and Watershed LRS
Enable Integrations or automations with these events of VectorShift and Watershed LRS
Actions
Create Pipeline
Creates a new VectorShift pipeline with the provided name and optional description.
List Pipelines
Retrieve the pipelines available to the current user. Optional parameters: include pipelines shared with you and return full pipeline objects instead of only IDs.
Run pipeline
Run a VectorShift pipeline with provided inputs and return the run results.
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Frequently Asked Questions
To start, connect both your VectorShift and Watershed LRS accounts to viaSocket. Once connected, you can set up a workflow where an event in VectorShift triggers actions in Watershed LRS (or vice versa).
Absolutely. You can customize how VectorShift data is recorded in Watershed LRS. This includes choosing which data fields go into which fields of Watershed LRS, setting up custom formats, and filtering out unwanted information.
The data sync between VectorShift and Watershed LRS 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 VectorShift and Watershed LRS. 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 VectorShift
VectorShift is an advanced AI platform designed to enhance data analysis and visualization. It leverages cutting-edge machine learning algorithms to transform complex datasets into actionable insights, making it an essential tool for businesses looking to optimize their decision-making processes.
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About Watershed LRS
Watershed LRS is a learning analytics platform that provides actionable insights from your training and performance data.
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