Reducing RAG Pipeline Latency for Real-Time Voice Conversations

TL;DR: Retrieval Augmented Generation (RAG) systems aim to reduce latency in real-time voice interactions for applications like customer service and enterprise search by optimizing various components such as speech-to-text, information retrieval, LLM processing, and text-to-speech services. To achieve low latency, RAG systems use techniques like vector search, caching, and streaming models, which enable near-instantaneous retrieval and generation of responses. By implementing these optimization strategies, organizations can drastically reduce latency in voice applications using the RAG pipeline, ensuring smoother and more efficient real-time conversations.