Beyond Retrieval: Modeling Confidence Decay and Deterministic Agentic Platforms in Generative Engine Optimization

Researchers propose a new approach to Generative Engine Optimization (GEO) that moves beyond current RAG-based systems to deterministic multi-agent platforms. The study introduces mathematical models for confidence decay in LLMs and demonstrates near-zero hallucination rates through specialized agent routing in industrial applications.