Category: Amazon Q

In this post, we discuss how you can use AWS HealthScribe with Amazon Q Business to create a chatbot to quickly gain insights into patient clinician conversations.

Amazon Q Business recently added support for administrators to modify the default access control list (ACL) crawling feature for data source connectors. Amazon Q Business is a fully managed, AI powered assistant with enterprise-grade security and privacy features. It includes over 40 data source connectors that crawl and index documents. By default, Amazon Q Business […]

In this post, we will demonstrate how to set up Slack connector for Amazon Q Business to sync communications from both public and private channels, reflective of user permissions.

In this post, we explore how Amazon Q Business uses personalization to improve the relevance of responses and how you can align your use cases and end-user data to take full advantage of this capability

In this post we show how you can quickly launch generative AI-enabled expert chatbots, trained on your proprietary document sets, to empower your workforce across specific aerospace roles with Amazon Q and Amazon Bedrock.

In this post, we present a real-world use case analyzing the Diabetes 130-US hospitals dataset to develop an ML model that predicts the likelihood of readmission after discharge.

In this blog post, we explore how you can use Amazon Q Business to build generative AI assistants that enhance employee experience and boost productivity. Amazon Q Business seamlessly integrates with internal data sources, knowledge bases, and productivity tools to equip your workforce with instant access to information, automated tasks, and personalized support.

In this post we describe how AWS generative AI solutions (including Amazon Bedrock, Amazon Q Developer, and Amazon Q Business) can further enhance TechOps productivity, reduce time to resolve issues, enhance customer experience, standardize operating procedures, and augment knowledge bases.

In this post, we show you how to perform natural language queries over the indexed GitHub (Cloud) data using the AI-powered chat interface provided by Amazon Q Business. We also cover how Amazon Q Business applies access control lists (ACLs) associated with the indexed documents to provide permissions-filtered responses.

In this post, we demonstrate how to create an Amazon Q Business application and index website contents using the Amazon Q Web Crawler connector for Amazon Q Business. We use two data sources (websites) here. The first data source is an employee onboarding guide from a fictitious company, which requires basic authentication. We demonstrate how to set up authentication for the Web Crawler. The second data source is the official documentation for Amazon Q Business. For this data source, we demonstrate how to apply advanced settings to instruct the Web Crawler to crawl only pages and links related to Amazon Q Business.