Overcoming RAG Limitations with Awarity’s Elastic Context Window
Introduction Retrieval-Augmented Generation (RAG) has emerged as a popular technique to enhance the capabilities of large language models (LLMs) by combining their generative power with the ability to access and retrieve information from external knowledge sources. While RAG has shown promise in various applications, scaling it to handle the massive datasets encountered in enterprise environments […]
Navigating the Challenges of Context Window Limitations
In the deployment of Large Language Models (LLMs), context windows define the amount of data a model can process at any given time. While this might sound like a minor technical detail, it directly impacts the quality of insights generated—especially when working with enterprise-level datasets that can easily reach tens of gigabytes. For many […]