Tag: Azure AI Document Intelligence

• Exploring AI Agent-Driven Auto Insurance Claims RAG Pipeline.

  

  Introduction: In this post, I explore a recent experiment aimed at creating a RAG pipeline tailored for the insurance industry, specifically for handling automobile insurance claims, with the goal of potentially reducing processing times. I also showcase the implementation of Autogen AI Agents to enhance search retrieval through agent interaction and function calls on sample…

  jbernec

  September 1, 2024

  Agent-based RAG

  ai-agents, autogen, Azure, Azure AI Document Intelligence, azure ai search, chunking, embedding, generative ai, insurance-rag, LLM, Microsoft, RAG, ResponsibleAI, Retrieval Augmented Generation, vector store

• Enhancing Document Extraction with Azure AI Document Intelligence and LangChain for RAG Workflows.

  

  Overview. The broadening of conventional data engineering pipelines and applications to include document extraction and preprocessing for unstructured PDFs, audio, and video files is becoming more prevalent. This shift is propelled by the increasing demand for advanced generative AI applications in businesses, adhering to the RAG (Retrievable Augmented Generation) model. In this post, I will…

  jbernec

  July 10, 2024

  Retrieval Augment Generation

  Azure AI Document Intelligence, Azure AI Studio, Azure Open Ai, LangChain, LLMs, RAG, Retrieval Augmented Generation, Semantic Kernel