Why RAG Exists
Understanding the limitations of traditional LLMs
AI
Thinking...
Knowledge Cutoff
Training data has a cutoff date. LLMs cannot access information after their training.
"What happened in 2024?"
❌ Cannot answer accurately
Hallucinations
LLMs can confidently generate false or fabricated information.
"Cite sources for this claim"
⚠️ May invent references
No Private Data
Cannot access your company's documents, databases, or proprietary information.
"Check our internal docs"
🔒 No access to private data
The RAG Solution
Retrieval Augmented Generation
RAG enhances LLMs by retrieving relevant knowledge from external sources before generating answers.
Instead of relying solely on training data, RAG systems dynamically fetch up-to-date, relevant information to ground their responses in factual data.
🧠
LLM
📚
Knowledge