All news with #amazon bedrock tag

🚀 Beginning today, Amazon Bedrock is available in the Israel (Tel Aviv) region, enabling customers to build and scale generative AI applications with local infrastructure. The managed service connects organizations to a variety of foundation models (FMs) and provides tools to deploy and operate agents, reducing time-to-production. Local availability can lower latency, support regional compliance needs, and help move projects from experimentation to real-world deployment.

🚀 Amazon has launched Amazon Bedrock in the Asia Pacific (Thailand), Asia Pacific (Malaysia), and Asia Pacific (Taipei) regions, enabling local customers to build and scale generative AI applications using a range of foundation models and developer tools. The managed service supports deploying agents and productionizing models to shorten the path from experimentation to real-world deployment. Customers can expect improved latency, regional data residency options, and integration with AWS operational and security services.

🔒 This post presents an architecture to enforce strong, source-of-truth authorization for Retrieval-Augmented Generation (RAG) knowledge bases using Amazon S3 Access Grants with Amazon Bedrock. It explains why vector DB metadata filtering is insufficient—permission changes can be delayed and complex identity memberships are hard to represent—and recommends validating permissions at the data source before returning chunks to an LLM. The blog includes a practical Python walkthrough for exchanging identity tokens, retrieving caller grant scopes, filtering returned chunks, and logging withheld items to reduce the risk of sensitive data leaking into LLM prompts.

🔒 Amazon Q Developer CLI now supports remote MCP servers to centralize tool integrations and OAuth-based authentication, enhancing scalability and security in development workflows. Administrators specify HTTP transport, the authentication URL, and optional headers in agent configuration or mcp.json. Upon successful OAuth authentication, the CLI enumerates tools on the MCP server and exposes them to the agent. This capability is available in both the CLI and the Amazon Q Developer IDE plugins.

🖼️ Amazon Bedrock now includes Stability AI Image Services, a suite of nine specialized image-editing tools available via the Bedrock API. The offering splits into Edit tools (Remove Background, Erase Object, Search and Replace, Search and Recolor, Inpaint) and Control tools (Structure, Sketch, Style Guide, Style Transfer). It is currently supported in US West (Oregon), US East (N. Virginia), and US East (Ohio), and is intended to accelerate professional creative workflows with granular edit control.

🚀 AWS has expanded availability of OpenAI open weight models on Amazon Bedrock to eight additional regions. The update adds US East (N. Virginia), Asia Pacific (Tokyo), Europe (Stockholm), Asia Pacific (Mumbai), Europe (Ireland), South America (São Paulo), Europe (London), and Europe (Milan) to the previously supported US West (Oregon). This broader regional coverage reduces network latency, helps meet data residency preferences, and makes it easier for customers to deploy AI-powered applications closer to their users. Customers can access the models through the Amazon Bedrock console and supporting documentation to get started.

🔍 DeepSeek-V3.1 is now available as a fully managed foundation model in Amazon Bedrock, offering an open-weight option designed for enterprise deployment. The model supports a selectable 'thinking' mode for step-by-step analysis and a faster non-thinking mode for quicker replies, with improved multilingual accuracy and reduced hallucinations. Enhanced tool-calling, transparent reasoning, and strong coding and analytical performance make it well suited for building AI agents, automating workflows, and tackling complex technical tasks. DeepSeek-V3.1 is available in US West (Oregon), Asia Pacific (Tokyo, Mumbai), and Europe (London, Stockholm).

🤖 Amazon Web Services added four Qwen3 open-weight foundation models to Amazon Bedrock as fully managed, serverless offerings. The lineup—Qwen3-Coder-480B-A35B-Instruct, Qwen3-Coder-30B-A3B-Instruct, Qwen3-235B-A22B-Instruct-2507, and Qwen3-32B—covers both dense and Mixture-of-Experts (MoE) architectures. The coder variants specialize in agentic coding, function calling, and tool use, while the 235B and 32B models provide general reasoning and efficient dense computation. These models are available now across multiple AWS regions, enabling developers to build advanced AI applications without managing infrastructure.

🚀 AWS has expanded availability of OpenAI open weight models on AWS Bedrock to eight additional AWS Regions worldwide. The update brings the models to US East (N. Virginia), Asia Pacific (Tokyo, Mumbai), Europe (Stockholm, Ireland, London, Milan) and South America (São Paulo), alongside existing US West (Oregon) support. This broader footprint aims to lower latency, improve model performance and help customers meet data residency requirements. To get started, use the Amazon Bedrock console or consult the documentation.

🔍 Amazon has added disk-optimized vector storage to OpenSearch Serverless, offering a lower-cost alternative to memory-optimized vectors while maintaining equivalent accuracy and recall. The disk-optimized option may introduce slightly higher latency, so it is best suited for semantic search, recommendation systems, and other AI search scenarios that do not require sub-millisecond responses. As a fully managed service, OpenSearch Serverless continues to automatically scale compute capacity (measured in OCUs) to match workload demands.

🚀 Amazon Bedrock now offers an on-demand deployment option for customized Meta Llama 3.3 models that have been fine-tuned or distilled in Bedrock; models customized on or after September 15, 2025 are eligible. The feature lets customers process requests in real time and pay only for consumed compute, removing the need for pre-provisioned always-on resources. Bedrock continues to provide a managed platform with built-in security, privacy, and responsible AI capabilities.

🔒 AWS announced that Amazon Bedrock AgentCore Gateway now supports AWS PrivateLink for private VPC access and adds invocation logging to Amazon CloudWatch, Amazon S3, and Amazon Data Firehose. These updates allow agent traffic to avoid the public internet while sending per-invocation logs to common observability and storage services. The combination improves network isolation, governance, and operational visibility. AgentCore Gateway is currently in preview in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Frankfurt).

⚡ Amazon Bedrock now supports synchronous inference for TwelveLabs Marengo Embed 2.7, delivering low-latency text and image embeddings directly in API responses. Previously optimized for asynchronous processing of large video, audio, and image files, Marengo 2.7’s new mode enables responsive search and retrieval features—such as instant natural-language video search and image similarity discovery—while retaining advanced video understanding via asynchronous workflows.

🔐 AWS introduced three new IAM condition keys that let administrators govern API keys for Amazon Bedrock. The keys control which services can be issued service-specific credentials, the maximum allowable age of long-term Bedrock API keys at creation, and whether requests use short-term or long-term bearer tokens. These controls are available in all AWS Regions and are documented in the IAM and Bedrock User Guides.

🔁 Anthropic's Claude Sonnet 4 is now available with Global cross‑Region inference in Amazon Bedrock, allowing inference requests to be routed to any supported commercial AWS Region for processing. The Global profile helps optimize compute resources and distribute traffic to increase model throughput. It supports both on‑demand and batch inference and is intended for use cases that do not require geography‑specific routing.

🚀 Amazon announced the general availability of Amazon Bedrock in the Asia Pacific Jakarta region, enabling customers to build and scale generative AI applications closer to end users. The fully managed service exposes a selection of high-performing foundation models via a single API and includes capabilities such as Guardrails and Model customization. These features are designed to help organizations incorporate security, privacy, and responsible AI into production workflows while accelerating development and deployment.

🧠 Amazon Web Services announced integration of Amazon Neptune with Zep, an open-source memory server for LLM applications, enabling persistent long-term memory and contextual history. Developers can use Neptune Database or Neptune Analytics as the graph store and Amazon OpenSearch as the text-search layer within Zep’s memory system. The integration enables graph-powered retrieval, multi-hop reasoning, and hybrid search across graph, vector, and keyword modalities, simplifying the creation of personalized, context-aware LLM agents.

⚡Amazon Bedrock updated prompt caching for Anthropic’s Claude models—Claude 3.5 Haiku, Claude 3.7, and Claude 4—to simplify cache management. Developers now set a single cache breakpoint at the end of a request and the system automatically reads the longest previously cached prefix, removing manual segment selection and reducing integration complexity. By excluding cache read tokens from TPM quotas, this change can free up token capacity and lower costs for multi-turn workflows. The capability is available today in all regions offering these Claude models; enable caching in your Bedrock model invocations and refer to the Bedrock Developer Guide for details.

🔍 Amazon Web Services announced general availability of Bring Your Own Knowledge Graph (BYOKG) support for Retrieval-Augmented Generation (RAG) using the open-source GraphRAG Toolkit. Developers can now connect domain-specific graphs stored in Amazon Neptune (Database or Analytics) directly to LLM workflows, combining graph queries with vector search. This reduces hallucinations and improves multi-hop and temporal reasoning, easing operationalization of graph-aware generative AI.

📄 Amazon Web Services' Bedrock Data Automation now supports five additional document languages — Portuguese, French, Italian, Spanish, and German — expanding multilingual document processing beyond English. Customers can build blueprints, prompts, and instructions in these languages using BDA Custom Output, while BDA Standard Output will produce summaries and figure captions in the detected document language. This update is generally available across multiple AWS commercial and GovCloud regions and aims to accelerate multilingual document workflows for intelligent document processing and multimodal automation.