AWSML

Organizations are increasingly integrating generative AI capabilities into their applications to enhance customer experiences, streamline operations, and drive innovation. As generative AI workloads continue to grow in scale and importance, organizations face new challenges in maintaining consistent performance, reliability, and availability of their AI-powered applications. Customers are looking to scale their AI inference workloads across … Read more

Agentic AI applications represent a significant development in enterprise automation, where intelligent agents autonomously execute complex workflows, access sensitive datasets, and make real-time decisions across your organization’s infrastructure. Amazon Bedrock AgentCore accelerates enterprise AI transformation by providing fully managed services that remove infrastructure complexity, maintain session isolation, and enable seamless integration with enterprise tools so … Read more

This post was written with Meghana Chintalapudi and Surabhi Sankhla of Kore.ai. As organizations struggle with exponentially growing volumes of data distributed across multiple repositories and applications, employees lose significant time—approximately 30% according to the International Data Corporation (IDC)—searching for information that could be spent on higher-value work. The complexity of modern enterprise data networks … Read more

Today, we’re excited to announce the Amazon Bedrock AgentCore Model Context Protocol (MCP) Server. With built-in support for runtime, gateway integration, identity management, and agent memory, the AgentCore MCP Server is purpose-built to speed up creation of components compatible with Bedrock AgentCore. You can use the AgentCore MCP server for rapid prototyping, production AI solutions, … Read more

This post is cowritten with Thomas Voss and Bernhard Hersberger from Hapag-Lloyd. Hapag-Lloyd is one of the world’s leading shipping companies with more than 308 modern vessels, 11.9 million TEUs (twenty-foot equivalent units) transported per year, and 16,700 motivated employees in more than 400 offices in 139 countries. They connect continents, businesses, and people through … Read more

This post was co-written with Shriram Sridharan, Taeuk Kang, and Santhosh Kumar Manavasi Lakshminarayanan from Rox. Rox is building a new revenue operating system for the applied AI era. Modern revenue teams rely on more data than ever before, such as Customer Relationship Management (CRM) systems, marketing automation, finance systems, support tickets, and live product … Read more

Fraud continues to cause significant financial damage globally, with U.S. consumers alone losing $12.5 billion in 2024—a 25% increase from the previous year according to the Federal Trade Commission. This surge stems not from more frequent attacks, but from fraudsters’ increasing sophistication. As fraudulent activities become more complex and interconnected, conventional machine learning approaches fall short … Read more

This blog was co-authored with Kuldeep Singh, Head of AI Platform at Innovaccer. The integration of agentic AI is ushering in a transformative era in health care, marking a significant departure from traditional AI systems. Agentic AI demonstrates autonomous decision-making capabilities and adaptive learning in complex medical environments, enabling it to monitor patient progress, coordinate … Read more

Site reliability engineers (SREs) face an increasingly complex challenge in modern distributed systems. During production incidents, they must rapidly correlate data from multiple sources—logs, metrics, Kubernetes events, and operational runbooks—to identify root causes and implement solutions. Traditional monitoring tools provide raw data but lack the intelligence to synthesize information across these diverse systems, often leaving … Read more

Today, we are excited to announce support for DoWhile loops in Amazon Bedrock Flows. With this powerful new capability, you can create iterative, condition-based workflows directly within your Amazon Bedrock flows, using Prompt nodes, AWS Lambda functions, Amazon Bedrock Agents, Amazon Bedrock Flows inline code, Amazon Bedrock Knowledge Bases, Amazon Simple Storage Service (Amazon S3), … Read more

This post was written with Lucas Dahan, Dil Dolkun, and Mathew Ng from PropHero. PropHero is a leading property wealth management service that democratizes access to intelligent property investment advice through big data, AI, and machine learning (ML). For the Spanish and Australian consumer base, PropHero needed an AI-powered advisory system that could engage customers … Read more

In the benefits administration industry, claims processing is a vital operational pillar that makes sure employees and beneficiaries receive timely benefits, such as health, dental, or disability payments, while controlling costs and adhering to regulations like HIPAA and ERISA. Businesses aim to optimize the workflow—covering claim submission, validation, adjudication, payment, and appeals—to enhance employee satisfaction, … Read more

AI agents are evolving beyond basic single-task helpers into more powerful systems that can plan, critique, and collaborate with other agents to solve complex problems. Deep Agents—a recently introduced framework built on LangGraph—bring these capabilities to life, enabling multi-agent workflows that mirror real-world team dynamics. The challenge, however, is not just building such agents but … Read more

This post is co-written by Mark Warner, Principal Solutions Architect for Thales, Cyber Security Products. As generative AI applications make their way into production environments, they integrate with a wider range of business systems that process sensitive customer data. This integration introduces new challenges around protecting personally identifiable information (PII) while maintaining the ability to … Read more

This post was written with Sarah Ostermeier from Comet. As enterprise organizations scale their machine learning (ML) initiatives from proof of concept to production, the complexity of managing experiments, tracking model lineage, and managing reproducibility grows exponentially. This is primarily because data scientists and ML engineers constantly explore different combinations of hyperparameters, model architectures, and … Read more

Building an AI agent that can handle a real-life use case in production is a complex undertaking. Although creating a proof of concept demonstrates the potential, moving to production requires addressing scalability, security, observability, and operational concerns that don’t surface in development environments. This post explores how Amazon Bedrock AgentCore helps you transition your agentic applications … Read more

This post was written with Alex Gnibus of Stability AI. Stability AI Image Services are now available in Amazon Bedrock, offering ready-to-use media editing capabilities delivered through the Amazon Bedrock API. These image editing tools expand on the capabilities of Stability AI’s Stable Diffusion 3.5 models (SD3.5) and Stable Image Core and Ultra models, which … Read more

Amazon Bedrock now offers Stability AI Image Services: 9 tools that improve how businesses create and modify images. The technology extends Stable Diffusion and Stable Image models to give you precise control over image creation and editing. Clear prompts are critical—they provide art direction to the AI system. Strong prompts control specific elements like tone, … Read more

As organizations scale their use of generative AI, many workloads require cost-efficient, bulk processing rather than real-time responses. Amazon Bedrock batch inference addresses this need by enabling large datasets to be processed in bulk with predictable performance—at 50% lower cost than on-demand inference. This makes it ideal for tasks such as historical data analysis, large-scale … Read more

Organizations building custom machine learning (ML) models often have specialized requirements that standard platforms can’t accommodate. For example, healthcare companies need specific environments to protect patient data while meeting HIPAA compliance, financial institutions require specific hardware configurations to optimize proprietary trading algorithms, and research teams need flexibility to experiment with cutting-edge techniques using custom frameworks. … Read more

Generative AI solutions like Amazon Q Business are transforming the way employees work. Organizations in every industry are embracing these tools to help their workforce extract valuable insights from increasingly fragmented data to accelerate decision-making processes. However, the adoption of generative AI tools hasn’t been without its challenges. Two hurdles have emerged in the implementation … Read more

OpenAI has released two open-weight models, gpt-oss-120b (117 billion parameters) and gpt-oss-20b (21 billion parameters), both built with a Mixture of Experts (MoE) design and a 128K context window. These models are the leading open source models, according to Artificial Analysis benchmarks, and excel at reasoning and agentic workflows. With Amazon SageMaker AI, you can … Read more

This post is co-written with Samit Verma, Eusha Rizvi, Manmeet Singh, Troy Smith, and Corey Finley from Verisk. Verisk Rating Insights as a feature of ISO Electronic Rating Content (ERC) is a powerful tool designed to provide summaries of ISO Rating changes between two releases. Traditionally, extracting specific filing information or identifying differences across multiple … Read more

Organizations gain competitive advantage by deploying and integrating new generative AI models quickly through Generative AI Gateway architectures. This unified interface approach simplifies access to multiple foundation models (FMs), addressing a critical challenge: the proliferation of specialized AI models, each with unique capabilities, API specifications, and operational requirements. Rather than building and maintaining separate integration … Read more

Today, we are excited to announce a new capability of Amazon SageMaker HyperPod task governance to help you optimize training efficiency and network latency of your AI workloads. SageMaker HyperPod task governance streamlines resource allocation and facilitates efficient compute resource utilization across teams and projects on Amazon Elastic Kubernetes Service (Amazon EKS) clusters. Administrators can … Read more

This post is co-written with Stefan Walter from msg. With more than 10,000 experts in 34 countries, msg is both an independent software vendor and a system integrator operating in highly regulated industries, with over 40 years of domain-specific expertise. msg.ProfileMap is a software as a service (SaaS) solution for skill and competency management. It’s … Read more

Retrieval Augmented Generation (RAG) is a fundamental approach for building advanced generative AI applications that connect large language models (LLMs) to enterprise knowledge. However, crafting a reliable RAG pipeline is rarely a one-shot process. Teams often need to test dozens of configurations (varying chunking strategies, embedding models, retrieval techniques, and prompt designs) before arriving at … Read more

You can use Amazon Bedrock Custom Model Import to seamlessly integrate your customized models—such as Llama, Mistral, and Qwen—that you have fine-tuned elsewhere into Amazon Bedrock. The experience is completely serverless, minimizing infrastructure management while providing your imported models with the same unified API access as native Amazon Bedrock models. Your custom models benefit from … Read more

This post is co-written with Gareth Jones from Anthropic. Anthropic’s Claude 4 Sonnet model has launched on Amazon Bedrock, marking a significant advancement in foundation model capabilities. Consequently, the deprecation timeline for Anthropic’s Claude 3.5 Sonnet (v1 and v2) was announced. This evolution creates a dual imperative for production AI applications: the opportunity to harness … Read more

In real-world video and image analysis, businesses often face the challenge of detecting objects that weren’t part of a model’s original training set. This becomes especially difficult in dynamic environments where new, unknown, or user-defined objects frequently appear. For example, media publishers might want to track emerging brands or products in user-generated content; advertisers need … Read more