In this article, you will learn how to set up a personal Amazon WorkSpace with Simple AD to validate the Amazon WorkSpaces provisioning and sign-in experience without first implementing the intended Microsoft Entra ID-based architecture. It follows the actual console flow: create a directory, regist
Deploy your Strands Agent to Amazon Bedrock AgentCore Runtime for a fully managed, scalable solution! This guide walks you through using the AgentCore Starter Toolkit to package your agent, build a container image, and create necessary AWS resources. Learn how to configure, launch, and invoke your agent, laying the groundwork for an Enterprise Knowledge & Cost Copilot with future integrations.
Strands Agents SDK with MCP enables developers to connect to AWS MCP servers for documentation, pricing, and architectural assistance. Build Python agents to automate tasks, integrate AWS tools, and deliver faster AI solutions.
In this article, you will learn how to build an Agentic AI assistant using the Strands Agents SDK and FAISS-based memory
Learn how to build a responsible AI HR Assistant using Strands Agents SDK and Amazon Bedrock Guardrails to handle HR queries, block sensitive topics, and automate workflows with custom Python tools.
In this article, you'll learn how to build an Agentic AI Assistant using the Strands Agents SDK, integrated with Amazon DynamoDB, to manage support tickets. The assistant will support ticket creation, updates, and retrieval in real time.
Build an AI-powered insurance Q&A agent using Strands Agents SDK and Amazon Bedrock Knowledge Base to answer customer policy questions accurately, retrieve info from S3, and suggest human help when needed.
Build an AI agent using Strands Agents SDK to automate IT ticket classification. Utilize custom Python tools and Amazon Bedrock models to streamline support workflows, enhancing response accuracy and speed.
Learn how to create and configure Amazon Bedrock Guardrails using the Standard tier to secure multilingual AI apps, filter harmful content, block denied topics, and ensure global compliance and safety.
In this article, you will learn how to implement Amazon Bedrock ApplyGuardrail API using Python code to detect and mask the sensitive PII information.
Create and configure an Amazon Bedrock Knowledge Base connected to SharePoint Online using SharePoint App-Only authentication. Securely sync, test, and manage data to generate accurate, AI-powered responses with citation support.
Learn how to enhance enterprise search by connecting Amazon Bedrock Knowledge Bases with the Kendra GenAI index to enable AI-powered conversations, smarter document querying, and better SharePoint data access.
Learn how to create and configure an Amazon Kendra GenAI index using Microsoft OneDrive as a data source to enable powerful LLM-based semantic search with natural language understanding and precise results.
In this article, you will learn how to create and configure Amazon Bedrock Knowledge Base to connect to Microsoft Teams data.
Integrating Amazon Bedrock Knowledge Bases with an Amazon Kendra GenAI index enables AI-driven enterprise search, transforming document queries into interactive conversations with contextually relevant answers and source citations.
In this article, you will learn how to create and configure an Amazon Kendra GenAI index using SharePoint Online as a data source.
In this article, you will learn to implement the Amazon Bedrock ApplyGuardrail API in a .NET console application to validate content and ensure compliance with responsible AI policies.
This article shows you how to integrate AWS Lambda with Amazon Bedrock Prompt Flow to create an intelligent data retrieval and processing system. This solution helps you automate data processing and generate user-friendly summaries, improving efficiency and user experience.
In this article, you will learn how to build an Amazon Bedrock Prompt Flow to automate the retrieval and summarization of content from SharePoint Online using the AWS CLI.
In this article, you’ll learn how to automate the creation of a flow with a single prompt in Amazon Bedrock using the .NET console application.
This article walks you through setting up Bedrock, integrating it with C#, and making API calls to invoke AI models. Perfect for developers looking to leverage AWS AI services in .NET applications.
Learn how to automate AI workflow creation in Amazon Bedrock using AWS CLI. Set up IAM roles, define prompt flows, and integrate AWS services like Lambda and S3. Follow step-by-step commands to deploy and test your AI-powered flow.
Learn how to create and configure an Amazon Bedrock Knowledge Base using SharePoint Online as a data source. Set up authentication, sync data, and validate responses to generate accurate answers with citations.
Learn to create and manage prompts in Amazon Bedrock using a .NET console application. This guide covers setting up your environment with AWS CLI and Visual Studio, and using the AWSSDK.BedrockAgent package to create, list, get, version, and delete prompts. Essential for effective prompt management.
This article walks you through setting up AWS Lambda, configuring PowerShell scripts, and securely accessing SharePoint data. Streamline your workflows with a serverless approach for seamless SharePoint integration.
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