Category: Amazon Machine Learning

We launched constrained decoding to provide reliability when using tools for structured outputs. Now, tools can be used with Amazon Nova foundation models (FMs) to extract data based on complex schemas, reducing tool use errors by over 95%. In this post, we explore how you can use Amazon Nova FMs for structured output use cases.

In this post, we first introduce the Strands Agents SDK and its core features. Then we explore how it integrates with AWS environments for secure, scalable deployments, and how it provides rich observability for production use. Finally, we discuss practical use cases, and present a step-by-step example to illustrate Strands in action.

In this post, we introduce how to combine Strands Agents with Tavily’s purpose-built web intelligence API, to create powerful research agents that excel at complex information gathering tasks while maintaining the security and compliance standards required for enterprise deployment.

In this post, we show how you can build an automated, serverless solution to transform webinar recordings into comprehensive handouts using Amazon Bedrock Data Automation for video analysis. We walk you through the implementation of Amazon Bedrock Data Automation to transcribe and detect slide changes, as well as the use of Amazon Bedrock foundation models (FMs) for transcription refinement, combined with custom AWS Lambda functions orchestrated by AWS Step Functions.

This blog post explores how to create powerful agentic applications using the Amazon Bedrock FMs, LangGraph, and the Model Context Protocol (MCP), with a practical scenario of handling a GitHub workflow of issue analysis, code fixes, and pull request generation.

Today, we’re excited to announce that Mistral-Small-3.2-24B-Instruct-2506—a 24-billion-parameter large language model (LLM) from Mistral AI that’s optimized for enhanced instruction following and reduced repetition errors—is available for customers through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a capability in Amazon Bedrock that developers can use to discover, test, and use over […]

A suspicious transaction report (STR) or suspicious activity report (SAR) is a type of report that a financial organization must submit to a financial regulator if they have reasonable grounds to suspect any financial transaction that has occurred or was attempted during their activities. In this post, we explore a solution that uses FMs available in Amazon Bedrock to create a draft STR.

In this post, we present a complete solution for fine-tuning and deploying the Llama-3.2-11B-Vision-Instruct model for web automation tasks. We demonstrate how to build a secure, scalable, and efficient infrastructure using AWS Deep Learning Containers (DLCs) on Amazon Elastic Kubernetes Service (Amazon EKS).

In this post, we examine a solution adopted by Nippon Life India Asset Management Limited that improves the accuracy of the response over a regular (naive) RAG approach by rewriting the user queries and aggregating and reranking the responses. The proposed solution uses enhanced RAG methods such as reranking to improve the overall accuracy

In this post, we demonstrate how to create a powerful research assistant for drug discovery using Strands Agents and Amazon Bedrock. This AI assistant can search multiple scientific databases simultaneously using the Model Context Protocol (MCP), synthesize its findings, and generate comprehensive reports on drug targets, disease mechanisms, and therapeutic areas.