Start With the Right Problem
A RAG chatbot is useful when the answer already exists in your documents but people waste time finding it. That usually means policy lookups, SOP support, onboarding docs, product manuals, or internal procedures.
Core Architecture
Use document ingestion, chunking, embeddings, retrieval, a ranked context window, and a model response layer. Keep the retrieval layer separate from the answer layer so each can be tested independently.
Quality Controls
- Require citations for business-critical answers.
- Use confidence thresholds to refuse weak responses.
- Log unanswered queries for content gaps.
Deployment Checklist
Scope the corpus, define answer boundaries, tune chunk size, add eval prompts, and connect the assistant to a review path for high-risk queries.