Zero-Waste Agentic RAG: Designing Caching Architectures to Minimize Latency and LLM Costs at Scale

A novel caching architecture called Agentic RAG has been developed to significantly reduce large language model (LLM) operational costs by approximately 30%. This approach employs validation-aware, multi-tier caching strategies that optimize latency and resource utilization, enabling more cost-effective and scalable deployment of LLMs without compromising accuracy.