Deep Dive into Retrieval-Augmented Generation (RAG)

As businesses strive to enhance their AI capabilities, a key challenge is providing models with access to extensive and up-to-date information without exceeding token limits or compromising performance. Retrieval-Augmented Generation (RAG) has emerged as a solution to this problem. In this episode, we take a technical deep dive into RAG, discussing its advantages and disadvantages, and exploring how Officely AI integrates RAG within a broader AI strategy to deliver scalable and controlled solutions.