← Back to Glossary
Architecture
RAG (Retrieval-Augmented Generation)
Technique connecting an LLM to your own data for accurate answers.
Retrieval-Augmented Generation (RAG) is an architecture that enhances LLMs by allowing them to query an external knowledge base before answering. Instead of relying solely on what it 'memorized' during training (which may be outdated), RAG searches your PDFs, databases, or web, and uses that fresh, verified information to generate the response.
Examples
- An employee chatbot answering HR policy questions by consulting the company handbook.
- A legal assistant searching specific case law in a private database before drafting advice.
Use Cases
- Internal Enterprise Search.
- Customer support based on specific technical documentation.
- Academic research assistants.
Next paths
Go deeper from this topic
Move from educational content into the product, solution, and implementation pages that matter next.