This post is co-written with Keith Beaudoin and Nicolas Bordeleau from Coveo. As generative AI transforms business operations, enterprises face a critical challenge: how can they help large language models (LLMs) provide accurate and trustworthy responses? Without reliable data foundations, these AI models can generate misleading or inaccurate responses, potentiallyContinue Reading
Amazon Q Business is a generative AI-powered enterprise assistant that helps organizations unlock value from their data. By connecting to enterprise data sources, employees can use Amazon Q Business to quickly find answers, generate content, and automate tasks—from accessing HR policies to streamlining IT support workflows, all while respecting existingContinue Reading
Organizations want direct answers to their business questions without the complexity of writing SQL queries or navigating through business intelligence (BI) dashboards to extract data from structured data stores. Examples of structured data include tables, databases, and data warehouses that conform to a predefined schema. Large language model (LLM)-powered naturalContinue Reading
For an AI model to perform effectively in specialized domains, it requires access to relevant background knowledge. A customer support chat assistant, for instance, needs detailed information about the business it serves, and a legal analysis tool must draw upon a comprehensive database of past cases. To equip large languageContinue Reading
Customers need better accuracy to take generative AI applications into production. In a world where decisions are increasingly data-driven, the integrity and reliability of information are paramount. To address this, customers often begin by enhancing generative AI accuracy through vector-based retrieval systems and the Retrieval Augmented Generation (RAG) architectural pattern,Continue Reading
Amazon Kendra is an intelligent enterprise search service that helps you search across different content repositories with built-in connectors. AWS customers use Amazon Kendra with large language models (LLMs) to quickly create secure, generative AI–powered conversational experiences on top of your enterprise content. As enterprises adopt generative AI, many areContinue Reading
Retrieval Augmented Generation (RAG) is a technique that enhances large language models (LLMs) by incorporating external knowledge sources. It allows LLMs to reference authoritative knowledge bases or internal repositories before generating responses, producing output tailored to specific domains or contexts while providing relevance, accuracy, and efficiency. RAG achieves this enhancementContinue Reading
