Engineering Evidence‑Grounded Review Pipelines With Hybrid RAG and LLMs

Unchecked language generation is not a harmless bug — it is a costly liability in regulated domains.

• A single invented citation in a visa evaluation can derail an application and triggering months of appeal.
• A hallucinated clause in a compliance report can result in penalties.
• A fabricated reference in a clinical review can jeopardize patient safety.

Large language models (LLMs) are not “broken”; they are simply unaccountable. Retrieval‑augmented generation (RAG) helps, but standard RAG remains brittle: