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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Order
Triggers when a new order is created.
Do thisActions
Action is the task that follows automatically within your Starshipit integrations.
Create a Order
Create an outbound order.
List Shipped Orders
Retrieve details of orders that have been shipped.
Create an index
Create an index for vectors created with an external embedding model.
Generate vectors
Generate vector embeddings for input data.
Delete an Index
Removes a specified index by its ID or name.
Fetch Index by Name
Returns details and structure of a specified index.
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Frequently Asked Questions
To start, connect both your Starshipit and Pinecone accounts to viaSocket. Once connected, you can set up a workflow where an event in Starshipit triggers actions in Pinecone (or vice versa).
Absolutely. You can customize how Starshipit data is recorded in Pinecone. This includes choosing which data fields go into which fields of Pinecone, setting up custom formats, and filtering out unwanted information.
The data sync between Starshipit and Pinecone 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 Starshipit and Pinecone. 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 Starshipit
Starshipit is an integrated shipping and tracking software that helps businesses automate their shipping processes. The app allows users to manage orders, print shipping labels, and provide real-time tracking updates to customers, enhancing the efficiency of e-commerce operations.
Learn MoreAbout Pinecone
Pinecone is a vector database designed to provide fast and scalable similarity search and machine learning applications. It enables developers to build high-performance applications that require real-time vector search and retrieval, making it ideal for AI-driven solutions.
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