Connect Dromo and Pinecone to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Dromo
Choose an Action
Automatically do this!
Create an index
Generate vectors
Delete an Index
Fetch Index by Name
Enable Integrations or automations with these events of Dromo and Pinecone
Enable Integrations or automations with these events of Dromo and Pinecone
Actions
Get All Uploads
Fetch all the uploaded data.
List Import Schemas
List all the import schemas.
Get Import Schema
Retrieve a selected import schema
Delete an import schema
Remove the import schema.
Create Schema
Creates a new schema.
Create an index
Create an index for vectors created with an external embedding model.
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Frequently Asked Questions
To start, connect both your Dromo and Pinecone accounts to viaSocket. Once connected, you can set up a workflow where an event in Dromo triggers actions in Pinecone (or vice versa).
Absolutely. You can customize how Dromo 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 Dromo 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 Dromo 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 Dromo
Dromo is a powerful data import platform designed to simplify and streamline the process of importing data into applications. It offers a user-friendly interface and robust features to handle complex data import tasks efficiently, making it ideal for businesses looking to enhance their data management capabilities.
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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