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1. How Clarus Care uses Amazon Bedrock to deliver conversational contact center interactions

   In this post, we illustrate how Clarus Care, a healthcare contact center solutions provider, worked with the AWS Generative AI Innovation Center (GenAIIC) team to develop a generative AI-powered contact center prototype. This solution enables conversational interaction and multi-intent resolution through an automated voicebot and chat interface. It also incorporates a scalable service model to...

2. Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

   Evaluating the performance of large language models (LLMs) goes beyond statistical metrics like perplexity or bilingual evaluation understudy (BLEU) scores. For most real-world generative AI scenarios, it’s crucial to understand whether a model is producing better outputs than a baseline or an earlier iteration. This is especially important for applications such as summarization, content...

3. Simplify ModelOps with Amazon SageMaker AI Projects using Amazon S3-based templates

   This post explores how you can use Amazon S3-based templates to simplify ModelOps workflows, walk through the key benefits compared to using Service Catalog approaches, and demonstrates how to create a custom ModelOps solution that integrates with GitHub and GitHub Actions—giving your team one-click provisioning of a fully functional ML environment.

4. Scale AI in South Africa using Amazon Bedrock global cross-Region inference with Anthropic Claude 4.5 models

   In this post, we walk through how global cross-Region inference routes requests and where your data resides, then show you how to configure the required AWS Identity and Access Management (IAM) permissions and invoke Claude 4.5 models using the global inference profile Amazon Resource Name (ARN). We also cover how to request quota increases for your workload. By the end, you'll have a...

5. Scaling content review operations with multi-agent workflow

   The agent-based approach we present is applicable to any type of enterprise content, from product documentation and knowledge bases to marketing materials and technical specifications. To demonstrate these concepts in action, we walk through a practical example of reviewing blog content for technical accuracy. These patterns and techniques can be directly adapted to various content review needs...

6. Build reliable Agentic AI solution with Amazon Bedrock: Learn from Pushpay’s journey on GenAI evaluation

   In this post, we walk you through Pushpay's journey in building this solution and explore how Pushpay used Amazon Bedrock to create a custom generative AI evaluation framework for continuous quality assurance and establishing rapid iteration feedback loops on AWS.

7. Build an intelligent contract management solution with Amazon Quick Suite and Bedrock AgentCore

   This blog post demonstrates how to build an intelligent contract management solution using Amazon Quick Suite as your primary contract management solution, augmented with Amazon Bedrock AgentCore for advanced multi-agent capabilities.

8. 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.

9. How Totogi automated change request processing with Totogi BSS Magic and Amazon Bedrock

   This blog post describes how Totogi automates change request processing by partnering with the AWS Generative AI Innovation Center and using the rapid innovation capabilities of Amazon Bedrock.

10. Build AI agents with Amazon Bedrock AgentCore using AWS CloudFormation

    Amazon Bedrock AgentCore services are now being supported by various IaC frameworks such as AWS Cloud Development Kit (AWS CDK), Terraform and AWS CloudFormation Templates. This integration brings the power of IaC directly to AgentCore so developers can provision, configure, and manage their AI agent infrastructure. In this post, we use CloudFormation templates to build an end-to-end application...