RAG Tutorials Don't Teach You This | Must Watch

Why It Matters

Enterprises deploying RAG must add fine-grained, relationship-aware authorization to prevent data leaks from retrieval errors; integrating ReBAC (e.g., Ory FGA) into the RAG pipeline materially reduces compliance and security risk. Without this layer, LLM-based assistants can inadvertently expose sensitive internal documents despite correct role assignments.

Summary

In this tutorial, Abhishek explains retrieval-augmented generation (RAG) and highlights a critical enterprise security gap: vector databases and LLMs perform similarity search and generation but do not enforce fine-grained authorization, risking exposure of sensitive internal documents. He argues that traditional role-based access control (RBAC) is insufficient for dynamic, document-level permissions and advocates relationship-based access control (ReBAC) to model user-resource relationships. Abhishek demonstrates implementing ReBAC with Ory’s FGA to filter retrieved documents before they reach the LLM, ensuring only authorized content is used for responses. The video includes a walkthrough of signing up for Ory FGA and applying it to a sample smart HR assistant to show real-time enforcement.

Original Description

- Get started with Auth0 FGA for FREE:

http://a0.to/5j7

Everyone talks about embeddings, vector databases, chunking, and prompts in RAG systems.

Almost nobody talks about security and that is a serious problem.

In this video, we break down one of the biggest hidden risks in AI applications: authorization in RAG systems and AI assistants.

As enterprises adopt internal AI copilots and chatbots, your system can accidentally expose documents users should never have access to.

We’ll cover:

✅ What RAG actually is

✅ Why authorization matters in AI systems

✅ Why traditional RBAC is often not enough

✅ What ReBAC (Relationship Based Access Control) is

✅ How Auth0 FGA solves authorization for secure RAG

✅ A practical demo using Auth0’s official implementation guide

We’ll also look at how a secure RAG pipeline works and why vector search alone is NOT security.

If you're building:

• AI Assistants

• Enterprise Copilots

• Internal Chatbots

• Secure RAG Systems

• Multi tenant AI Platforms

This is something you need to understand before shipping to production.

🔗 Get started with Auth0 for FREE:

http://a0.to/5j7

Free Course on the channel

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About me:

========

Instagram: https://www.instagram.com/abhishekveeramalla_official/

Telegram Channel : https://t.me/abhishekveeramalla

LinkedIn: https://www.linkedin.com/in/abhishek-veeramalla

GitHub: https://github.com/iam-veeramalla

Medium: https://abhishekveeramalla-av.medium.com/

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