What is hallucination in LLMs and how do LLMOps systems mitigate it?

Hallucination is when LLMs generate plausible but incorrect information; LLMOps mitigates it using retrieval, guardrails, and evaluation.

Hallucinations occur because LLMs predict tokens based on probability, not factual verification. LLMOps reduces hallucinations using RAG pipelines, constrained decoding, fact-checking layers, and output validation models. Monitoring systems also track hallucination rates via human or automated evaluation.