---
description: Reference architectures and design guides that use Vectorize.
title: Architectures
image: https://developers.cloudflare.com/og-docs.png
---

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> Documentation Index  
> Fetch the complete documentation index at: https://developers.cloudflare.com/vectorize/llms.txt  
> Use this file to discover all available pages before exploring further.

# Architectures

Last updated Aug 24, 2026|Copy as Markdown|[View as Markdown](https://mchen-ai-models-sync.previews.developers.cloudflare.com/vectorize/demos/index.md)|[Agent setup](https://mchen-ai-models-sync.previews.developers.cloudflare.com/agent-setup/)

Learn how you can use Vectorize within your existing architecture.

## Reference architectures

Explore the following reference architectures that use Vectorize:

[**Fullstack applications**A practical example of how these services come together in a real fullstack application architecture.](https://mchen-ai-models-sync.previews.developers.cloudflare.com/reference-architecture/diagrams/serverless/fullstack-application/)

[**Ingesting BigQuery Data into Workers AI**You can connect a Cloudflare Worker to get data from Google BigQuery and pass it to Workers AI, to run AI Models, powered by serverless GPUs.](https://mchen-ai-models-sync.previews.developers.cloudflare.com/reference-architecture/diagrams/ai/bigquery-workers-ai/)

[**Composable AI architecture**The architecture diagram illustrates how AI applications can be built end-to-end on Cloudflare, or single services can be integrated with external infrastructure and services.](https://mchen-ai-models-sync.previews.developers.cloudflare.com/reference-architecture/diagrams/ai/ai-composable/)

[**Retrieval Augmented Generation (RAG)**RAG combines retrieval with generative models for better text. It uses external knowledge to create factual, relevant responses, improving coherence and accuracy in NLP tasks like chatbots.](https://mchen-ai-models-sync.previews.developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/)

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