The problem RAG solves
General AI models know a lot about the world but nothing specific about your business unless you tell them. Retrieval-augmented generation, or RAG, connects an AI model to a set of documents so it can find relevant information and use it in answers.
How it works simply
When someone asks a question, the system searches your documents for relevant passages, then gives those passages to the AI along with the question. The AI writes an answer based on that retrieved information.
Common business uses
- Answering employee questions from procedures and handbooks
- Helping customer service staff find policy details
- Searching through product information
- Summarizing information from many documents
Why it can be more accurate
Because answers are grounded in your documents, they can be more accurate and specific than general AI answers. Many systems can also show which document the answer came from.
Limits to remember
RAG is only as good as the documents behind it. Outdated or contradictory documents lead to wrong answers. The AI can still make mistakes, so important answers should be checked.
Easier options for small businesses
Many AI tools now let you upload documents to a project or workspace, which provides a simple version of this capability without technical setup.
Protect sensitive data
Be careful about which documents you upload and who can access the system.
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