AWS Blog

In this post, we demonstrate how to build an enterprise AI assistant solution that uses LLMs in Amazon Bedrock with the precision of enterprise knowledge bases using the RAG approach. By integrating AWS services such as Lambda and Amazon Bedrock, our solution enables organizations to securely access and retrieve proprietary data, providing contextually relevant and accurate responses. The RAG approach not only enhances the assistant’s ability to provide tailored responses within specific enterprise data domains, but also mitigates the risk of hallucinations. By injecting the latest enterprise proprietary knowledge into the response generation context, our solution makes sure that the assistant remains up-to-date and adaptable to evolving specific business needs. The sample code repository and CloudFormation template can enable organizations to streamline the development and deployment of their RAG-based AI assistant solutions.

AWS announces new integration capabilities for Amazon EventBridge and AWS Step Functions, enabling direct communication with private APIs using AWS PrivateLink and Amazon VPC Lattice. This enhancement streamlines secure application interactions across private networks, on-premises infrastructure, and cloud platforms, offering improved security, simplified architecture, and enhanced performance for enterprise-level deployments.

When implementing machine learning workflows in Amazon SageMaker Canvas, organizations might need to consider external dependencies required for their specific use cases. Although SageMaker Canvas provides powerful no-code and low-code capabilities for rapid experimentation, some projects might require specialized dependencies and libraries that aren’t included by default in SageMaker Canvas. This post provides an example of how to incorporate code that relies on external dependencies into your SageMaker Canvas workflows.

In this post, we explore how you can use Amazon Bedrock to generate high-quality categorical ground truth data, which is crucial for training machine learning (ML) models in a cost-sensitive environment. Generative AI solutions can play an invaluable role during the model development phase by simplifying training and test data creation for multiclass classification supervised learning use cases. We dive deep into this process on how to use XML tags to structure the prompt and guide Amazon Bedrock in generating a balanced label dataset with high accuracy. We also showcase a real-world example for predicting the root cause category for support cases. This use case, solvable through ML, can enable support teams to better understand customer needs and optimize response strategies.

Speed up build times on CodeBuild with test splitting across multiple parallel build environments. Read how test splitting with CodeBuild works and how to get started.

As enterprises scale their Kubernetes workloads on Amazon Elastic Kubernetes Service (Amazon EKS), they need effective cost and performance optimization. IBM Instana Observability (Instana), a comprehensive observability platform, and IBM Kubecost, a cost-monitoring solution for Kubernetes, work together to provide real-time visibility into both performance and cost metrics. The integration between IBM Instana and Kubecost [...]

Introduction Imagine you want to create intelligent text summarization tools without managing infrastructure. How can you efficiently build AI-powered solutions that can transform lengthy documents into concise summaries? Amazon Bedrock, a fully managed service from AWS, addresses this challenge by optimizing text summarization through its Converse API. The Converse API provides a standardized interface for [...]

In this post, we explain how Dynatrace provides end-to-end monitoring and visibility into generative AI applications utilizing Amazon Bedrock models allowing for comprehensive LLM observability.

Nearly 30,000 attendees were welcomed to the March 2025 Game Developers Conference (GDC) at the Moscone Convention Center with an official ribbon cutting by the Mayor of San Francisco. Games industry professionals, executive and enthusiasts visited the Amazon Web Services (AWS) for Games GDC booth to witness how the cloud, AI, and real-time streaming are [...]

Today we’re announcing the general availability (GA) of the new Amazon Cognito Identity Pool Level 2 (L2) construct in the AWS Cloud Development Kit (AWS CDK). This construct simplifies the creation and management of identity pools, permissions, and provider integrations by providing intent-based APIs that help users securely manage their authenticated and unauthenticated (guest) users [...]