Without RAG, AI chatbots hallucinate — they generate plausible but incorrect answers. Retrieval-augmented generation fixes this by searching your indexed documents before the AI composes a response.
How RAG works
When a customer asks a question, the system embeds the query, searches your knowledge base for relevant chunks, and includes those passages in the AI's context window. The model then generates an answer grounded in your actual content.
What to index
Product docs, pricing pages, FAQs, policy documents, API references, and internal playbooks. Keep content updated — stale knowledge bases lead to outdated answers.
CRAB's approach
Upload PDFs, Markdown files, and URLs directly. CRAB handles chunking, embedding, and retrieval automatically, with relevance scoring visible in the dashboard.