How do you prevent hallucinations in a MERN AI chatbot?

Four defence layers. First, RAG grounding: every answer cites specific documents from your knowledge base, retrieved via MongoDB Atlas Vector Search hybrid retrieval. Second, structured output constraints: force the LLM to return JSON with citation IDs, reject responses without them. Third, output guardrails: a classifier rejects responses making claims outside the retrieved context. Fourth, evaluation suite: 50 to 200 real questions with expected answers, scored on groundedness and relevance every deploy in CI. Hallucination in a MERN AI chatbot is a solvable engineering problem, not a mysterious LLM behaviour. Any chatbot vendor claiming otherwise is either lazy or selling you a service that skips these four steps.