1. Introduction Organizations generate vast amounts of unstructured data daily, including emails, PDFs, wikis, logs, and various other forms. Traditional machine learning models (LLMs) often struggle to process these data silos effectively at scale due to several challenges, such as latency, governance issues, and token limit constraints. Retrieval-Augmented Generation (RAG)

Designing Intelligent LLM Systems for Real-Time Decision Making As organizations grapple with ever-growing volumes of data and rising expectations for real-time decision-making, agentic systems powered by large language models (LLMs) are emerging as a transformative solution.  Databricks stands out as a versatile platform, seamlessly integrating data processing, governance, and model