From RAG to Agentic Systems: When Retrieval Isn't Enough

Retrieval-augmented generation (RAG) effectively enhances large language models by providing context through document retrieval, making it suitable for answering questions, summarizing knowledge bases, and generating contextual content. However, in enterprise SaaS environments, RAG's capabilities are limited as it cannot execute actions, operate on real-time system states, or enforce tool-level authorization. This is where agentic systems come into play, expanding upon RAG by integrating a reasoning loop, tool-calling capabilities, structured API access, and multi-step execution, thus enabling operations such as updating CRM records and initiating workflows. These agentic systems necessitate explicit authorization checks and real-time data access to ensure secure and accurate execution within enterprise systems. Unified serves as a data access layer across various SaaS categories, providing both retrieval and action capabilities while maintaining security and compliance through structured APIs and permission-aware execution. The progression from RAG to agentic systems involves incorporating live API retrieval, tool-calling for execution, and robust authorization mechanisms to transform chatbots into comprehensive operational AI systems.