---
title: "Discussion on \"Your RAG Agent Is Quoting Deleted Documents (Postgres + pgvector Fix)\" | Hashnode"
description: "Discussion on \"Your RAG Agent Is Quoting Deleted Documents (Postgres + pgvector Fix)\". Your RAG agent quoted a deleted contract because its embedding lived in a separate vector database. Keep embeddings in Postgres with pgvector."
url: "https://hashnode.com/posts/your-rag-agent-is-quoting-deleted-documents-postgres-pgvector-fix/6af87c4d73981077371cce5c"
---

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# [Your RAG Agent Is Quoting Deleted Documents (Postgres + pgvector Fix)](https://nodeneuralai.hashnode.dev/your-rag-agent-is-quoting-deleted-documents-postgres-pgvector-fix?utm_source=hashnode&utm_medium=feed)

Your RAG agent quoted a deleted contract because its embedding lived in a separate vector database. Keep embeddings in Postgres with pgvector.

4h ago · 6 min read · nodeneuralai.hashnode.dev  
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-   [#postgresql](https://hashnode.com/tag/postgresql)
-   [#pgvector](https://hashnode.com/tag/pgvector)
-   [#artificial-intelligence](https://hashnode.com/tag/artificial-intelligence)
-   [#software-architecture](https://hashnode.com/tag/software-architecture)

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Enterprise AI architecture, explained with working code.

Enterprise AI architecture, explained with working code. Each article takes one problem teams hit when they put LLMs into real systems (ERP integrations, RAG, semantic caching, LLM routing) and shows a design that holds up in production. Videos on YouTube (@NodeNeuralAI), code on GitHub.

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