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Primer’s Retrieval-Augmented Generation-Verification (RAG-V) helps solve a critical issue with Large Language Models (LLMs): 'hallucinations,' or outputs that seem accurate but are misleading. With a 100x reduction in these errors, RAG-V delivers more reliable insights. Authored by Primer’s VP of Data Science, John Bohannon—a former NATO-embedded journalist known for simplifying complex tech—this whitepaper details RAG-V’s impact.