Category: Amazon Q

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 show you how to configure Amazon Bedrock Knowledge Bases with SharePoint Online as a data source. By connecting SharePoint Online as a data source, employees can interact with the organization’s knowledge and data stored in SharePoint using natural language, making it straightforward to find relevant information, extract key points, and derive valuable insights.

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.

Amazon Q Business is a conversational assistant powered by generative artificial intelligence (AI) that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems, which each user is authorized to access. In an earlier post, we discussed how you can build private and secure enterprise generative AI applications with Amazon Q Business and AWS IAM Identity Center. If you want to use Amazon Q Business to build enterprise generative AI applications, and have yet to adopt organization-wide use of AWS IAM Identity Center, you can use Amazon Q Business IAM Federation to directly manage user access to Amazon Q Business applications from your enterprise identity provider (IdP), such as Okta or Ping Identity. Amazon Q Business IAM Federation uses Federation with IAM and doesn’t require the use of IAM Identity Center. This post shows how you can use Amazon Q Business IAM Federation for user access management of your Amazon Q Business applications.