The Evolution of RAG Systems
Business data is a complex landscape, scattered across various platforms like Slack, Google Drive, and meeting transcripts. Prior to 2023, managing unstructured data was a challenge, often limited to simple text searches like Ctrl+F. Structured data was easier to handle through database queries, but the majority of organizational data remained unstructured.
This article delves into the evolution of retrieval augmented generation (RAG) systems, addressing their initial limitations and the shift towards more advanced architectures such as Agentic RAG and Semantic Caching. It emphasizes the significance of organizing structured data, the functions of different components within these new systems, and how advancements have overcome issues seen in previous models.
Implementing Agentic RAG Systems
By integrating real-time data querying with intelligent routing and retrieval strategies, agentic RAG systems pave the way for enhanced business insights. These systems offer a more sophisticated approach to handling unstructured data, enabling organizations to extract valuable knowledge from their vast repositories.
For further details and insights, you can read the full blog post here.
