Vectorize

Vectorize is a SaaS platform that automates data extraction from several sources and lets you quickly deploy real-time RAG pipelines for your unstructured data. It also includes evaluation to help figure out the best strategies for the RAG system.

Vectorize pipelines natively integrate with Qdrant by converting unstructured data into vector embeddings and storing them in a collection. When a pipeline is running, any new change in the source data is immediately processed, keeping the vector index up-to-date.

Prerequisites

  1. A Qdrant instance to connect to. You can get a free cloud instance at cloud.qdrant.io.
  2. An account at Vectorize.io for building those seamless pipelines.

Set Up

  • From the Vectorize dashboard, click Vector Databases -> New Vector Database Integration and select Qdrant.

  • Set up a connection using the hostname and API key of your Qdrant instance.

Vectorize connection

  • You can now select this Qdrant instance when setting up a RAG pipeline. Enter the name of the collection to use. It’ll be created automatically if it doesn’t exist.

Vectorize collection

  • Select an embeddings provider.

Vectorize Embeddings

  • Select a source from which to ingest data.

Vectorize Sources

Your Vectorize pipeline powered by Qdrant should now be up and ready to be scheduled and monitored.

Further Reading

Was this page useful?

Thank you for your feedback! 🙏

We are sorry to hear that. 😔 You can edit this page on GitHub, or create a GitHub issue.