Overview

Reader (RAG) is a technique that merges the capabilities of large language models with external information retrieval systems, enabling these models to dynamically access and incorporate data from databases or the internet.

By doing so, RAG enhances the accuracy and relevance of responses generated by AI agents in real-time, addressing limitations where static knowledge could be outdated or insufficient.

Key aspects

In 2026, as enterprises increasingly adopt agentic AI for customer service and knowledge management, RAG will become a standard feature. It allows AI systems to provide up-to-date information without needing constant updates from developers.

Frameworks like Haystack and libraries such as LangChain are expected to play pivotal roles in implementing RAG techniques within enterprise applications, ensuring that AI-driven interfaces remain knowledgeable and responsive.