Category: Intermediate (200)

In this post, we show you how to build an ecommerce product recommendation chatbot using HAQM Bedrock Agents and foundation models (FMs) available in HAQM Bedrock.

In this post, we delve into the process of building and deploying a sample application capable of generating multilingual descriptions for multiple images with a Streamlit UI, AWS Lambda powered with the HAQM Bedrock SDK, and AWS AppSync driven by the open source Generative AI CDK Constructs.

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 HAQM Q Business. We also cover how HAQM Q Business applies access control lists (ACLs) associated with the indexed documents to provide permissions-filtered responses.

In this post, we demonstrate how to seamlessly automate the deployment of an end-to-end RAG solution using Knowledge Bases for HAQM Bedrock and the AWS Cloud Development Kit (AWS CDK), enabling organizations to quickly set up a powerful question answering system.

In this post, we demonstrate how to create an HAQM Q Business application and index website contents using the HAQM Q Web Crawler connector for HAQM 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 HAQM 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 HAQM Q Business.

In this post, we will harness the power of generative artificial intelligence (AI) and HAQM Bedrock to help organizations simplify and effectively manage remediations of AWS Security Hub control findings.

Through this series of posts, we share our generative AI journey and use cases, detailing the architecture, AWS services used, lessons learned, and the impact of these solutions on our teams and customers. In this first post, we explore Account Summaries, one of our initial production use cases built on HAQM Bedrock. Account Summaries equips our teams to be better prepared for customer engagements. It combines information from various sources into comprehensive, on-demand summaries available in our CRM or proactively delivered based on upcoming meetings. From the period of September 2023 to March 2024, sellers leveraging GenAI Account Summaries saw a 4.9% increase in value of opportunities created.

HAQM 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 HAQM Q Business and AWS IAM Identity Center. If you want to use HAQM Q Business to build enterprise generative AI applications, and have yet to adopt organization-wide use of AWS IAM Identity Center, you can use HAQM Q Business IAM Federation to directly manage user access to HAQM Q Business applications from your enterprise identity provider (IdP), such as Okta or Ping Identity. HAQM 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 HAQM Q Business IAM Federation for user access management of your HAQM Q Business applications.

In this post, we provide an overview of HAQM Q Business Confluence Cloud connector and how you can use it for seamless integration of generative AI assistance to your Confluence Cloud.

In this post, we show you how to convert Python code that fine-tunes a generative AI model in HAQM Bedrock from local files to a reusable workflow using HAQM SageMaker Pipelines decorators.