---
title: Cloudflare Vectorize
description: Build full-stack AI applications with Vectorize, Cloudflare's vector database.
order: 0

pcx_content_type: overview
tags:
  - AI
sidebar:
  order: 1
head:
  - tag: title
    content: Overview
products:
  - vectorize
---

import {
	CardGrid,
	Description,
	Feature,
	LinkTitleCard,
	Plan,
	RelatedProduct,
	Render,
} from "~/components";

<Description>

Build full-stack AI applications with Vectorize, Cloudflare's powerful vector database.

</Description>

Vectorize is a globally distributed vector database that enables you to build full-stack, AI-powered applications with [Cloudflare Workers](/workers/). Vectorize makes querying embeddings — representations of values or objects like text, images, audio that are designed to be consumed by machine learning models and semantic search algorithms — faster, easier and more affordable.

<Render file="vectorize-ga" product="vectorize" />

For example, by storing the embeddings (vectors) generated by a machine learning model, including those built-in to [Workers AI](/workers-ai/) or by bringing your own from platforms like [OpenAI](#), you can build applications with powerful search, similarity, recommendation, classification and/or anomaly detection capabilities based on your own data.

The vectors returned can reference images stored in Cloudflare R2, documents in KV, and/or user profiles stored in D1 — enabling you to go from vector search result to concrete object all within the Workers platform, and without standing up additional infrastructure.

---

## Features

<Feature header="Vector database" href="/vectorize/get-started/intro/" cta="Create your Vector database">

Learn how to create your first Vectorize database, upload vector embeddings, and query those embeddings from [Cloudflare Workers](/workers/).

</Feature>

<Feature header="Vector embeddings using Workers AI" href="/vectorize/get-started/embeddings/" cta="Create vector embeddings using Workers AI">

Learn how to use Vectorize to generate vector embeddings using Workers AI.

</Feature>

<Feature header="Search using Vectorize and AI Search" href="/ai-search/" cta="Build a RAG with Vectorize">

Learn how to automatically index your data and store it in Vectorize, then query it to generate context-aware responses using AI Search.

</Feature>

---

## Related products

<RelatedProduct header="Workers AI" href="/workers-ai/" product="workers-ai">

Run machine learning models, powered by serverless GPUs, on Cloudflare’s global network.

</RelatedProduct>

<RelatedProduct header="R2 Storage" href="/r2/" product="r2">

Store large amounts of unstructured data without the costly egress bandwidth fees associated with typical cloud storage services.

</RelatedProduct>

---

## More resources

<CardGrid>

<LinkTitleCard
	title="Limits"
	href="/vectorize/platform/limits/"
	icon="document"
>
	Learn about Vectorize limits and how to work within them.
</LinkTitleCard>

<LinkTitleCard title="Use cases" href="/use-cases/ai/" icon="document">
	Learn how you can build and deploy ambitious AI applications to Cloudflare's
	global network.
</LinkTitleCard>

<LinkTitleCard
	title="Storage options"
	href="/workers/platform/storage-options/"
	icon="document"
>
	Learn more about the storage and database options you can build on with
	Workers.
</LinkTitleCard>

<LinkTitleCard
	title="Developer Discord"
	href="https://discord.cloudflare.com"
	icon="discord"
>
	Connect with the Workers community on Discord to ask questions, join the
	`#vectorize` channel to show what you are building, and discuss the platform
	with other developers.
</LinkTitleCard>

<LinkTitleCard
	title="@CloudflareDev"
	href="https://x.com/cloudflaredev"
	icon="x.com"
>
	Follow @CloudflareDev on Twitter to learn about product announcements, and
	what is new in Cloudflare Developer Platform.
</LinkTitleCard>

</CardGrid>
