RAG citation verification is a commonly overlooked failure point in production retrieval-augmented generation systems, according to the article, which builds core components of a TypeScript middleware library that replaces probabilistic matching with deterministic byte-span grounding assertions. The article says retrieval and generation are decoupled stages: a retriever surfaces relevant chunks from a vector store, but the LLM synthesizes its response independently, producing citations that may not correspond to any specific passage in the retrieved documents, and may paraphrase, truncate, merge fragments from different chunks, or fabricate a reference entirely. It cites examples including a hallucinated citation to a nonexistent case ruling creating liability in legal research tools, a misattributed drug interaction reference influencing clinical decisions in medical knowledge bases, and ungrounded citations as potential audit failures in enterprise document systems governed by compliance audits. The article states probabilistic similarity measures cannot provide the binary guarantee these domains require: either the cited text exists at that exact location in the source, or it does not. It describes building the library’s core components, benchmarked through Vitest to demonstrate sub-millisecond verification throughput for a fixture set of 1,000 citations across 50 documents totaling roughly 200 KB, while noting actual performance depends on hardware, document size, and citation density.