Artificial Intelligence
Author: Jiten Dedhia
Jiten is a leader in AI at Amazon Web Services (AWS), specializing in agentic AI for the advertising and marketing sector. He brings experience working with clients across financial services, life sciences, and telecom industries. He partners with C-suite leaders on AI strategy and transformation while guiding technical teams through enterprise-scale generative AI implementations.
Answer questions from tables embedded in documents with Amazon Q Business
Amazon Q Business launched support for tabular search, which you can use to extract answers from tables embedded in documents ingested in Amazon Q Business. Tabular search is a built-in feature in Amazon Q Business that works seamlessly across many domains, with no setup required from admin or end users. In this post, we ingest different types of documents that have tables and show you how Amazon Q Business responds to questions related to the data in the tables.
Query structured data from Amazon Q Business using Amazon QuickSight integration
In this post, we show how Amazon Q Business integrates with QuickSight to enable users to query both structured and unstructured data in a unified way. The integration allows users to connect to over 20 structured data sources like Amazon Redshift and PostgreSQL, while getting real-time answers with visualizations. Amazon Q Business combines information from structured sources through QuickSight with unstructured content to provide comprehensive answers to user queries.
Index your web crawled content using the new Web Crawler for Amazon Kendra
In this post, we show how to index information stored in websites and use the intelligent search in Amazon Kendra to search for answers from content stored in internal and external websites. In addition, the ML-powered intelligent search can accurately get answers for your questions from unstructured documents with natural language narrative content, for which keyword search is not very effective.