RAG

What is RAG in Gen AI — and Why Should You Care?

RAG = Retrieval-Augmented Generation

It’s a game-changer when it comes to combining LLMs + real-time data.
Instead of just relying on pre-trained knowledge, RAG allows your AI to fetch relevant context from your data (PDFs, docs, databases) before answering a question.

Example:

You ask: “What’s our Azure cost trend last quarter?”
Traditional LLM: “I don’t have real-time data.”
RAG-powered LLM: Fetches your cost reports → reads them → gives a context-aware answer.

How It Works (Simplified):

User Question →
Retrieve relevant chunks from your data using embeddings →
Feed into LLM as context →
LLM generates a much more accurate + personalized response

Why It Matters:
Keeps LLMs up-to-date
Reduces hallucinations
Makes GenAI enterprise-ready

Want to explore RAG with a practical lens?
Check out the full post: kasdevtech.com/ai/rag