Category: Intermediate (200)

In this post, we show how organizations in the public sector can automate their email management using a generative AI solution powered by Amazon Bedrock.

In this post, you build and connect that server end to end. You will implement MCP tools, set up two-layer JSON Web Token (JWT) authentication, deploy with AWS Cloud Development Kit (AWS CDK), and connect the result to Mistral AI’s Vibe. The post also covers prerequisites, solution architecture, best practices for MCP servers and Vibe connectors, and resource cleanup. The ecommerce server that you build supports product search, order placement, review submission, and returns processing using Amazon DynamoDB for data and Amazon Cognito for identity management.

This post is for data architects, business intelligence (BI) engineers, and analytics engineers building or optimizing Quick Sight Topics for natural-language Chat-based exploration.

In this post, we walk through how multi-dataset Topics work, explain how the chat agent uses defined relationships to generate cross-dataset queries, and demonstrate an end-to-end implementation using a retail analytics scenario in Quick Sight.

In this post, we walk through how to get started with MiniMax models on Amazon Bedrock, including the capabilities supported by these models, the service tiers available, how on-demand inference scales to handle your workloads, and the different APIs you can use to access them. Using these models, customers can build agentic applications, long-context document analysis pipelines, and software engineering workflows, all backed by the security and operational guarantees of AWS.

We’re excited to introduce US-based frontier open-weight models in AWS GovCloud (US). With this release, Amazon Bedrock now supports OpenAI’s open-weight GPT OSS models (120B and 20B) and NVIDIA Nemotron (Nano 9B v2, Nano 12B v2, Nano 30B, Super 120B) models. In this post, we cover these models and their capabilities, the inference options for data residency, the available service tiers and how to get started.

In this post, you will learn how Inscribe developed an agentic AI system using Amazon Bedrock that reasons across documents the way an expert fraud analyst would. With this new agentic AI system, Inscribe now detects tampered, fabricated, and AI-generated financial documents in under 90 seconds. This is a 20x improvement over traditional manual review, while maintaining the accuracy and explainability required by financial services regulations.

The Amazon Bedrock Model Profiler is an open source tool that aggregates model metadata from multiple AWS APIs and external sources into a single, searchable interface. In this post, you’ll learn what the Model Profiler provides, the real-world scenarios it supports, and how to deploy it in your own environment in under five minutes.

In this post, we demonstrate how to deploy BoltzGen on SageMaker AI and run an end-to-end protein design experiment. By the end of the walkthrough, you have a working setup that scales from quick validation runs to production batch processing. The setup offers two execution modes for different stages of research and uses step-level caching to reduce compute expenses during iterative workflows.

Today, we’re excited to announce the availability of Anthropic’s most advanced Sonnet model, Claude Sonnet 5, on Amazon Bedrock and Claude Platform on AWS. Claude Sonnet 5 is the first Sonnet model of Anthropic’s latest generation and represents a meaningful step forward. It delivers top-tier intelligence at Sonnet pricing for coding, agents, and everyday professional […]