Make Large Language Models Work–Without the Errors

Large language models (LLMs) have incredible potential, yet they’re prone to 'hallucinations'—outputs that seem accurate but are actually incorrect. Primer’s Retrieval-Augmented Generation-Verification (RAG-V) breaks new ground, reducing these errors by 100x to help you get dependable, actionable insights from your LLMs.

What You’ll Learn:

• Mission-critical accuracy: How to significantly reduce LLM errors through a verification process we call RAG-V
• The future of LLM-powered analysis: Why this technology is gaining traction in national security and high-stakes decision-making