RAG

Most people think LLMs “know everything.”

Reality? They don’t—they predict based on training data.
That’s where RAG changes the game.

👉 Instead of relying only on pre-trained knowledge, RAG systems:

Pull real-time, relevant data
Ground responses in actual documents
Reduce hallucinations significantly

🔍 What’s happening under the hood?

Data is ingested & converted into embeddings
Stored in a vector database (like Pinecone, Milvus)
User query → converted into embedding
System retrieves relevant context
LLM generates a fact-based response

💡 Why it matters:

Access to private & up-to-date data
More accurate and reliable outputs
Enables enterprise-grade AI applications

📊 From chatbots to internal knowledge systems—RAG is powering the next wave of AI.