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Merge pull request #1451 from qdrant/vectorize-video

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[docs] Vectorize Video
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David Myriel
2025-02-05 06:28:37 -05:00
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qdrant-landing/content/documentation/platforms/_index.md
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| [Portable.io](/documentation/platforms/portable/) | Cloud platform for developing and deploying ELT transformations. |
| [PrivateGPT](/documentation/platforms/privategpt/) | Tool to ask questions about your documents using local LLMs emphasising privacy. |
| [Rivet](/documentation/platforms/rivet/) | A visual programming environment for building AI agents with LLMs. |
| [Vectorize](/documentation/platforms/vectorize/) | Platform to automate data extraction, RAG evaluation, deploy RAG pipelines. |
| [Vectorize.io](/documentation/platforms/vectorize/) | Platform to automate data extraction, RAG evaluation, deploy RAG pipelines. |
qdrant-landing/content/documentation/platforms/vectorize.md
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title: Vectorize
title: Vectorize.io
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# Vectorize
# Vectorize.io
[Vectorize](https://vectorize.io/) is a SaaS platform that automates data extraction from [several sources](https://docs.vectorize.io/integrations/source-connectors) 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.
## Watch the Video
<p align="center"><iframe width="560" height="315" src="https://www.youtube.com/embed/zHJ3TZmKEeY?si=3kTq4q2Ot0o_2g2T" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe></p>
## Prerequisites
1. A Qdrant instance to connect to. You can get a free cloud instance at [cloud.qdrant.io](https://cloud.qdrant.io/).