Artificial Intelligence
Category: Amazon Cognito
Build a FinOps agent using Amazon Bedrock AgentCore
In this post, you learn how to build a FinOps agent using Amazon Bedrock AgentCore that helps your finance team manage AWS costs across multiple accounts. This conversational agent consolidates data from AWS Cost Explorer, AWS Budgets, and AWS Compute Optimizer into a single interface, so your team can ask questions like “What are my top cost drivers this month?” and receive immediate answers.
Building an AI powered system for compliance evidence collection
In this post, we show you how to build a similar system for your organization. You will learn the architecture decisions, implementation details, and deployment process that can help you automate your own compliance workflows.
Integrating Amazon Bedrock AgentCore with Slack
In this post, we demonstrate how to build a Slack integration using AWS Cloud Development Kit (AWS CDK). You will learn how to deploy the infrastructure with three specialized AWS Lambda functions, configure event subscriptions properly to handle Slack’s security requirements, and implement conversation management patterns that work for many agent use cases.
Embed Amazon Quick Suite chat agents in enterprise applications
Organizations find it challenging to implement a secure embedded chat in their applications and can require weeks of development to build authentication, token validation, domain security, and global distribution infrastructure. In this post, we show you how to solve this with a one-click deployment solution to embed the chat agents using the Quick Suite Embedding SDK in enterprise portals.
Accelerate agentic application development with a full-stack starter template for Amazon Bedrock AgentCore
In this post, you will learn how to deploy Fullstack AgentCore Solution Template (FAST) to your Amazon Web Services (AWS) account, understand its architecture, and see how to extend it for your requirements. You will learn how to build your own agent while FAST handles authentication, infrastructure as code (IaC), deployment pipelines, and service integration.
Build a serverless AI Gateway architecture with AWS AppSync Events
In this post, we discuss how to use AppSync Events as the foundation of a capable, serverless, AI gateway architecture. We explore how it integrates with AWS services for comprehensive coverage of the capabilities offered in AI gateway architectures. Finally, we get you started on your journey with sample code you can launch in your account and begin building.
Voice AI-powered drive-thru ordering with Amazon Nova Sonic and dynamic menu displays
In this post, we’ll demonstrate how to implement a Quick Service Restaurants (QSRs) drive-thru solution using Amazon Nova Sonic and AWS services. We’ll walk through building an intelligent system that combines voice AI with interactive menu displays, providing technical insights and implementation guidance to help restaurants modernize their drive-thru operations.
Build a device management agent with Amazon Bedrock AgentCore
In this post, we explore how to build a conversational device management system using Amazon Bedrock AgentCore. With this solution, users can manage their IoT devices through natural language, using a UI for tasks like checking device status, configuring WiFi networks, and monitoring user activity.
Create a private workforce on Amazon SageMaker Ground Truth with the AWS CDK
In this post, we present a complete solution for programmatically creating private workforces on Amazon SageMaker AI using the AWS Cloud Development Kit (AWS CDK), including the setup of a dedicated, fully configured Amazon Cognito user pool.
Build a scalable containerized web application on AWS using the MERN stack with Amazon Q Developer – Part 1
In a traditional SDLC, a lot of time is spent in the different phases researching approaches that can deliver on requirements: iterating over design changes, writing, testing and reviewing code, and configuring infrastructure. In this post, you learned about the experience and saw productivity gains you can realize by using Amazon Q Developer as a coding assistant to build a scalable MERN stack web application on AWS.









