---
title: "Discussion on \"RAG in Practice: Building a Citation-Grounded Search System \nwith pgvector and Amazon Bedrock\" | Hashnode"
description: "Discussion on \"RAG in Practice: Building a Citation-Grounded Search System \nwith pgvector and Amazon Bedrock\". Build a citation-grounded RAG pipeline using pgvector on Aurora Serverless v2, Amazon Bedrock, and Streamlit. Includes a RAG ON vs OFF demo."
url: "https://hashnode.com/posts/rag-in-practice-building-a-citation-grounded-search-system-with-pgvector-and-amazon-bedrock/69d45a5d5d075878b5cdf411"
---

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# [RAG in Practice: Building a Citation-Grounded Search System with pgvector and Amazon Bedrock](https://easyharshmods.hashnode.dev/rag-in-practice-building-a-citation-grounded-search-system-with-pgvector-and-amazon-bedrock?utm_source=hashnode&utm_medium=feed)

Build a citation-grounded RAG pipeline using pgvector on Aurora Serverless v2, Amazon Bedrock, and Streamlit. Includes a RAG ON vs OFF demo.

Apr 7 · 14 min read · easyharshmods.hashnode.dev  
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-   [#aws](https://hashnode.com/tag/aws)
-   [#rag](https://hashnode.com/tag/rag)
-   [#pgvector](https://hashnode.com/tag/pgvector)
-   [#bedrock](https://hashnode.com/tag/bedrock)
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-   [#generative-ai](https://hashnode.com/tag/generative-ai)
-   [#aurora](https://hashnode.com/tag/aurora)
-   [#streamlit](https://hashnode.com/tag/streamlit)

## Written by

[Harshwardhan Choudhary](https://hashnode.com/@easyharshmods)

@easyharshmods · Netherlands

  
[View profile](https://hashnode.com/@easyharshmods)

Cloud & DevOps Engineer crafting scalable serverless solutions

Passionate cloud architect specializing in AWS serverless architectures and infrastructure as code. I help organizations build and scale their cloud infrastructure using modern DevOps practices. With expertise in AWS Lambda, Terraform, and data engineering, I focus on creating efficient, cost-effective solutions. Currently based in the Netherlands, working on projects that push the boundaries of cloud computing and automation.

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