Amazon Web Services announces Claude Sonnet 4.5 in Amazon Bedrock, featuring advanced capabilities in coding, tool handling, and long-horizon tasks, with improvements in memory management, context processing, and industry-specific applications across finance, research, and cybersecurity sectors.

Amazon Nova Multimodal Embeddings is a new state-of-the-art embedding model available in Amazon Bedrock. It is the industry’s first embedding model that supports text, documents, images, video, and audio through a single unified model, enabling cross-modal retrieval and semantic search applications with leading accuracy, at industry-leading costs.

Amazon Bedrock Data Automation (BDA) now supports AVI, MKV, and WEBM file formats along with the AV1 and MPEG-4 Visual (Part 2) codecs, enabling you to generate structured insights across a broader range of video content. Additionally, BDA delivers up to 50% faster image processing. BDA automates the generation of insights from unstructured multimodal content such as documents, images, audio, and videos for your GenAI-powered applications. With support for AVI, MKV, and WEBM formats, you can now analyze content from archival footage, high-quality video archives with multiple audio tracks and subtitles, and web-based and open-source video content. This expanded video format and codec support enables you to process video content directly in the formats your organization uses, streamlining your workflows and accelerating time-to-insight. With faster image processing on BDA, you you can extract insights from visual content faster than ever before. You can now analyze larger volumes of images in less time, helping you scale your AI applications and deliver value to your customers more quickly. Amazon Bedrock Data Automation is available in 8 AWS regions: Europe (Frankfurt), Europe (London), Europe (Ireland), Asia Pacific (Mumbai), Asia Pacific (Sydney), US West (Oregon) and US East (N. Virginia), and GovCloud (US-West) AWS Regions. To learn more, see the https://docs.aws.amazon.com/bedrock/latest/userguide/bda.html and the https://aws.amazon.com/bedrock/pricing/ page. To get started with using Bedrock Data Automation, visit the https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#overview.

Amazon Bedrock Data Automation (BDA) now supports AVI, MKV, and WEBM file formats along with the AV1 and MPEG-4 Visual (Part 2) codecs, enabling you to generate structured insights across a broader range of video content. Additionally, BDA delivers up to 50% faster image processing. BDA automates the generation of insights from unstructured multimodal content such as documents, images, audio, and videos for your GenAI-powered applications. With support for AVI, MKV, and WEBM formats, you can now analyze content from archival footage, high-quality video archives with multiple audio tracks and subtitles, and web-based and open-source video content. This expanded video format and codec support enables you to process video content directly in the formats your organization uses, streamlining your workflows and accelerating time-to-insight. With faster image processing on BDA, you you can extract insights from visual content faster than ever before. You can now analyze larger volumes of images in less time, helping you scale your AI applications and deliver value to your customers more quickly. Amazon Bedrock Data Automation is available in 8 AWS regions: Europe (Frankfurt), Europe (London), Europe (Ireland), Asia Pacific (Mumbai), Asia Pacific (Sydney), US West (Oregon) and US East (N. Virginia), and GovCloud (US-West) AWS Regions. To learn more, see the Bedrock Data Automation User Guide and the Amazon Bedrock Pricing page. To get started with using Bedrock Data Automation, visit the Amazon Bedrock console.

AWS launches DeepSeek-V3.1 as a fully managed models in Amazon Bedrock. DeepSeek-V3.1 is a hybrid open weight model that switches between thinking mode for detailed step-by-step analysis and non-thinking mode for faster responses.

Amazon Bedrock has expanded its model offerings with the addition of Qwen 3 foundation models enabling users to access and deploy them in a fully managed, serverless environment. These models feature both mixture-of-experts (MoE) and dense architectures to support diverse use cases including advanced code generation, multi-tool business automation, and cost-optimized AI reasoning.

Today, we are excited to announce that Amazon SageMaker notebook instance supports https://aws.amazon.com/linux/amazon-linux-2023. You can now choose Amazon Linux 2023 for your new Amazon SageMaker notebook instance to take advantage of the latest innovations, enhanced security features. https://docs.aws.amazon.com/sagemaker/latest/dg/nbi.html are fully managed Jupyter Notebooks with pre-configured development environments for data science and machine learning. Data scientists and developers can use SageMaker Notebooks to interactively explore, visualize and prepare data, and build and deploy machine learning models on SageMaker. Amazon Linux 2023 (AL2023) is a general-purpose rpm-based Linux distribution and successor to Amazon Linux 2 (AL2). Amazon Linux 2023 simplifies operating system management through its secure, stable, and high-performance runtime environment. This Linux distribution follows a predictable two-year major release cycle with five years of long-term support. The first two years provide standard support with quarterly security patches, bug fixes, and new features, followed by three years of maintenance. Enhanced security features include SELinux support and FIPS 140-3 validation for cryptographic modules. With this you now have the options to launch a notebook instance with AL2023 or AL2. For more details about this launch and instructions on how to get started with AL2023 notebook instances, please refer to the https://docs.aws.amazon.com/sagemaker/latest/dg/nbi.html.

Today, we are excited to announce that Amazon SageMaker notebook instance supports Amazon Linux 2023. You can now choose Amazon Linux 2023 for your new Amazon SageMaker notebook instance to take advantage of the latest innovations, enhanced security features. Amazon SageMaker notebook instances are fully managed Jupyter Notebooks with pre-configured development environments for data science and machine learning. Data scientists and developers can use SageMaker Notebooks to interactively explore, visualize and prepare data, and build and deploy machine learning models on SageMaker. Amazon Linux 2023 (AL2023) is a general-purpose rpm-based Linux distribution and successor to Amazon Linux 2 (AL2). Amazon Linux 2023 simplifies operating system management through its secure, stable, and high-performance runtime environment. This Linux distribution follows a predictable two-year major release cycle with five years of long-term support. The first two years provide standard support with quarterly security patches, bug fixes, and new features, followed by three years of maintenance. Enhanced security features include SELinux support and FIPS 140-3 validation for cryptographic modules. With this you now have the options to launch a notebook instance with AL2023 or AL2. For more details about this launch and instructions on how to get started with AL2023 notebook instances, please refer to the Amazon Linux 2023 documentation.

Amazon Bedrock now offers Cohere Embed v4, the latest state-of-the-art multimodal embedding model from Cohere that produces high-quality embeddings for text, images, and complex business documents. This powerful addition to Amazon Bedrock enables enterprises to build AI applications with frontier search and retrieval capabilities. Traditional embedding models often struggle to understand complex multimodal business materials, such as business presentations and sales and financial reports, requiring extensive data pre-processing pipelines. Embed v4 addresses this challenge by natively processing documents with tables, graphs, diagrams, code snippets, and even handwritten notes. The model handles real-world imperfections such as spelling errors and formatting issues, eliminating the need for time-consuming data cleanup and helping you surface insights from previously difficult-to-search information. With support for over 100 languages, including Arabic, English, French, Japanese, and Korean, Embed v4 enables global organizations to seamlessly search for information, breaking language barriers. The model is also fine-tuned for industries such as finance, healthcare, and manufacturing, delivering superior performance on specialized documents including financial reports, medical records, and product specifications. Cohere Embed v4 is available for on-demand inference in US East (N. Virginia), Europe (Ireland), and Asia Pacific (Seoul), and can be accessed from select public AWS Regions through cross-region inference. Review thehttps://docs.aws.amazon.com/bedrock/latest/userguide/models-regions.html for complete regional availability. To get started, visit the https://signin.aws.amazon.com/signup?request_type=register to request model access. For more information, refer to the https://aws.amazon.com/bedrock/cohere/ and https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-cohere.html.

Amazon Bedrock now offers Cohere Embed v4, the latest state-of-the-art multimodal embedding model from Cohere that produces high-quality embeddings for text, images, and complex business documents. This powerful addition to Amazon Bedrock enables enterprises to build AI applications with frontier search and retrieval capabilities. Traditional embedding models often struggle to understand complex multimodal business materials, such as business presentations and sales and financial reports, requiring extensive data pre-processing pipelines. Embed v4 addresses this challenge by natively processing documents with tables, graphs, diagrams, code snippets, and even handwritten notes. The model handles real-world imperfections such as spelling errors and formatting issues, eliminating the need for time-consuming data cleanup and helping you surface insights from previously difficult-to-search information. With support for over 100 languages, including Arabic, English, French, Japanese, and Korean, Embed v4 enables global organizations to seamlessly search for information, breaking language barriers. The model is also fine-tuned for industries such as finance, healthcare, and manufacturing, delivering superior performance on specialized documents including financial reports, medical records, and product specifications. Cohere Embed v4 is available for on-demand inference in US East (N. Virginia), Europe (Ireland), and Asia Pacific (Seoul), and can be accessed from select public AWS Regions through cross-region inference. Review the Amazon Bedrock Model Support by Regions guide for complete regional availability. To get started, visit the Amazon Bedrock console to request model access. For more information, refer to the Cohere product page and documentation.

Beginning today, customers can use Amazon Bedrock in the Israel (Tel Aviv) region to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a comprehensive and secure service for building generative AI applications and agents. Amazon Bedrock connects you to leading foundation models (FMs) and services to deploy and operate agents, enabling you to quickly move from experimentation to real-world deployment. To get started, visit the https://aws.amazon.com/bedrock/ and see the https://docs.aws.amazon.com/bedrock/latest/userguide/models-regions.html for more details.

Beginning today, customers can use Amazon Bedrock in the Asia Pacific (Thailand), Asia Pacific (Malaysia), and Asia Pacific (Taipei) regions to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a comprehensive and secure service for building generative AI applications and agents. Amazon Bedrock connects you to leading foundation models (FMs) and services to deploy and operate agents, enabling you to quickly move from experimentation to real-world deployment. To get started, visit the https://aws.amazon.com/bedrock/ and see the https://docs.aws.amazon.com/bedrock/latest/userguide/models-regions.html for more details.

Beginning today, customers can use Amazon Bedrock in the Middle East (UAE) region to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a comprehensive and secure service for building generative AI applications and agents. Amazon Bedrock connects you to leading foundation models (FMs) and services to deploy and operate agents, enabling you to quickly move from experimentation to real-world deployment. To get started, visit the https://aws.amazon.com/bedrock/ and see the https://docs.aws.amazon.com/bedrock/latest/userguide/models-regions.html for more details.

Beginning today, customers can use Amazon Bedrock in the Asia Pacific (Thailand), Asia Pacific (Malaysia), and Asia Pacific (Taipei) regions to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a comprehensive and secure service for building generative AI applications and agents. Amazon Bedrock connects you to leading foundation models (FMs) and services to deploy and operate agents, enabling you to quickly move from experimentation to real-world deployment. To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.

Beginning today, customers can use Amazon Bedrock in the Israel (Tel Aviv) region to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a comprehensive and secure service for building generative AI applications and agents. Amazon Bedrock connects you to leading foundation models (FMs) and services to deploy and operate agents, enabling you to quickly move from experimentation to real-world deployment. To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.

Beginning today, customers can use Amazon Bedrock in the Middle East (UAE) region to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a comprehensive and secure service for building generative AI applications and agents. Amazon Bedrock connects you to leading foundation models (FMs) and services to deploy and operate agents, enabling you to quickly move from experimentation to real-world deployment. To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.

Amazon Web Services announces Claude Sonnet 4.5 in Amazon Bedrock, featuring advanced capabilities in coding, tool handling, and long-horizon tasks, with improvements in memory management, context processing, and industry-specific applications across finance, research, and cybersecurity sectors.

We’re excited today to announce the Amazon Nova Act extension - a tool that transforms how you build with Nova Act by bringing the entire agent development experience directly into IDEs like Visual Studio Code, Kiro, and Cursor. The Nova Act extension consolidates natural language based script creation, granular scripting precision, and robust browser testing into a single, unified user interface, eliminating the need to switch between multiple tools across development, validation, and iteration. The Nova Act extension is built on top of the Nova Act SDK, available in research preview since March 2025. The Nova Act extension addresses feedback we have received from developers and consolidates the agent development lifecycle, from ideation to production, into one unified user interface within your IDE. The Nova Act extension is available today from your IDE’s extension marketplace. The https://github.com/aws/nova-act-extension includes documentation and examples to get started. Learn more about the Nova Act extension and see the Nova Act extension in action https://aws.amazon.com/blogs/aws/accelerate-ai-agent-development-with-the-nova-act-ide-extension.

We’re excited today to announce the Amazon Nova Act extension - a tool that transforms how you build with Nova Act by bringing the entire agent development experience directly into IDEs like Visual Studio Code, Kiro, and Cursor. The Nova Act extension consolidates natural language based script creation, granular scripting precision, and robust browser testing into a single, unified user interface, eliminating the need to switch between multiple tools across development, validation, and iteration. The Nova Act extension is built on top of the Nova Act SDK, available in research preview since March 2025. The Nova Act extension addresses feedback we have received from developers and consolidates the agent development lifecycle, from ideation to production, into one unified user interface within your IDE. The Nova Act extension is available today from your IDE’s extension marketplace. The Nova Act GitHub repository includes documentation and examples to get started. Learn more about the Nova Act extension and see the Nova Act extension in action at our blog post.

AWS launches DeepSeek-V3.1 as a fully managed models in Amazon Bedrock. DeepSeek-V3.1 is a hybrid open weight model that switches between thinking mode for detailed step-by-step analysis and non-thinking mode for faster responses.

Amazon Bedrock has expanded its model offerings with the addition of Qwen 3 foundation models enabling users to access and deploy them in a fully managed, serverless environment. These models feature both mixture-of-experts (MoE) and dense architectures to support diverse use cases including advanced code generation, multi-tool business automation, and cost-optimized AI reasoning.

AWS HealthImaging now supports https://oauth.net/2/-compatible identity providers for authentication of DICOMweb requests using OpenID Connect (OIDC). With OIDC authentication, you can manage secure access to DICOM resources using your organization’s standard procedures for creating, enabling, and disabling user accounts. With this launch, you can now use existing identity providers (IdPs)—such as Amazon Cognito, Okta, or Auth0—to issue JSON Web Tokens (JWTs) that authorize secure access to your DICOMweb endpoints. This launch makes it simpler to integrate AWS HealthImaging into existing medical imaging applications and expands HealthImaging’s support of DICOMweb standard interfaces that rely on OAuth 2.0-compatible authentication. Support for OIDC is limited to DICOMweb REST API requests. HealthImaging includes native support for AWS Identity and Access Management (IAM) users and roles for authentication of all API requests. Support for OpenID Connect (OIDC) is available in all https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ where AWS HealthImaging is generally available: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more, visit https://docs.aws.amazon.com/healthimaging/latest/devguide/using-dicomweb.html.

AWS HealthImaging now supports OAuth 2.0-compatible identity providers for authentication of DICOMweb requests using OpenID Connect (OIDC). With OIDC authentication, you can manage secure access to DICOM resources using your organization’s standard procedures for creating, enabling, and disabling user accounts. With this launch, you can now use existing identity providers (IdPs)—such as Amazon Cognito, Okta, or Auth0—to issue JSON Web Tokens (JWTs) that authorize secure access to your DICOMweb endpoints. This launch makes it simpler to integrate AWS HealthImaging into existing medical imaging applications and expands HealthImaging’s support of DICOMweb standard interfaces that rely on OAuth 2.0-compatible authentication. Support for OIDC is limited to DICOMweb REST API requests. HealthImaging includes native support for AWS Identity and Access Management (IAM) users and roles for authentication of all API requests. Support for OpenID Connect (OIDC) is available in all AWS Regions where AWS HealthImaging is generally available: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more, visit Using DICOMweb with AWS HealthImaging.

Today, AWS announced the general availability of Custom Blueprints, a new feature in Amazon SageMaker Unified Studio, part of the next generation of Amazon SageMaker. This feature allows customers to use their own managed policies as per their corporate security requirements to create a project role in SageMaker Unified Studio. Customers can either replace the managed policies provide by Amazon SageMaker Unified Studio as part of the tooling blueprint with their custom policies or enrich the existing policies by appending additional policies. In addition to allowing you to bring your own managed policies, Custom Blueprints is designed to provide you the ability to configure the infrastructure and resources that you want to deploy in the project created in Amazon SageMaker Unified Studio. Using your own AWS CloudFormation templates you can define and customize the parameters and configuration for any AWS resources such as Amazon EMR on EC2, AWS Glue Data Catalog, and Amazon Redshift. You can replace the service managed blueprints with your custom blueprints in order to ensure standardization across your entire organization. The sample templates to create your custom blueprints are available https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/custom-blueprints.html. The ability to use Custom Blueprint is available in all AWS Commercial Regions where the next generation of Amazon SageMaker is available. See the https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/supported-regions.html for more details. For instructions on how to get started, visit the https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/custom-blueprints.html.

Today, AWS announced the general availability of Custom Blueprints, a new feature in Amazon SageMaker Unified Studio, part of the next generation of Amazon SageMaker. This feature allows customers to use their own managed policies as per their corporate security requirements to create a project role in SageMaker Unified Studio. Customers can either replace the managed policies provide by Amazon SageMaker Unified Studio as part of the tooling blueprint with their custom policies or enrich the existing policies by appending additional policies. In addition to allowing you to bring your own managed policies, Custom Blueprints is designed to provide you the ability to configure the infrastructure and resources that you want to deploy in the project created in Amazon SageMaker Unified Studio. Using your own AWS CloudFormation templates you can define and customize the parameters and configuration for any AWS resources such as Amazon EMR on EC2, AWS Glue Data Catalog, and Amazon Redshift. You can replace the service managed blueprints with your custom blueprints in order to ensure standardization across your entire organization. The sample templates to create your custom blueprints are available here. The ability to use Custom Blueprint is available in all AWS Commercial Regions where the next generation of Amazon SageMaker is available. See the supported regions list for more details. For instructions on how to get started, visit the Amazon SageMaker documentation.