All news with #amazon bedrock tag

🚀 AWS announces Amazon Aurora MySQL-Compatible Edition now integrates with Kiro Powers, enabling developers to build Aurora MySQL-backed applications faster using AI agent assistance. The integration bundles curated Model Context Protocol (MCP) servers, steering files, and hooks validated by Kiro partners to provide immediate expertise in Aurora MySQL operations and schema design via natural language. Developers can execute data plane and control plane tasks conversationally, while task-specific guidance prevents information overload. The feature is available via one-click installation from the Kiro IDE and webpage across all Regions that support Aurora MySQL.

🛈 Amazon Bedrock now supports request-level usage attribution on the InvokeModel and InvokeModelWithResponseStream APIs, enabling customers to tag individual model inference calls with attributes such as team, project, and environment. This capability extends existing attribution options like application inference profiles, IAM principal attribution, project-level tracking on bedrock-mantle, and workspace tracking for Anthropic Claude models. Customers can enable model invocation logging in their AWS Region and include metadata in requests to analyze usage in Bedrock model invocation logs. The feature is available in all AWS commercial Regions where Amazon Bedrock is offered.

🔒 Amazon explains how AgentCore Gateway enforces a centralized authorization layer between autonomous agents and external tools, treating the LLM as an untrusted actor. Policies are expressed in the open-source Cedar language for readability, bounded execution, and mathematical analyzability, enabling deterministic enforcement and formal verification during policy authoring and attachment. A neuro-symbolic workflow translates natural-language rules into Cedar, validates them with Cedar Analysis, and enforces decisions at runtime to constrain tool invocations and filter unavailable actions.

💬 AWS announces that Partner Central agents let partners create sales opportunities via natural language conversation instead of multi-step forms. Released March 16, 2026 and built on Amazon Bedrock AgentCore, the agents ingest meeting notes, proposals, and transcripts (PDF, DOCX, Excel, TXT), extract details, and recommend improvements. Accessible through Amazon Q chat in the AWS Console and programmatically via Model Context Protocol (MCP), they aim to reduce data entry, improve pipeline hygiene, and shorten sales cycles across all commercial AWS Regions.

🔒 The AWS AI Security Framework presents a structured model that helps security and business leaders align the right controls to the right use case, at the right layer, and at the right phase so AI can move from prototype to production securely. Its core principle is that you build AI on top of security, not add security later. The post maps controls across three layers—infrastructure, identity and data, and AI application—and across four use cases from answering to agentic and physical AI. It highlights Amazon Bedrock and AgentCore as pillars that decouple model choice from security infrastructure.

🔒 The updated AWS User Guide to Governance, Risk, and Compliance for Responsible AI Adoption provides Financial Services customers practical GRC guidance for deploying AI responsibly. It covers governance, risk management, compliance, data and model management, and AI agent oversight, and maps these considerations to AWS capabilities. The guide highlights services such as Amazon Bedrock AgentCore, Bedrock Guardrails, Bedrock Agents, SageMaker Autopilot, and SageMaker Model Monitor. It complements existing AWS responsible AI and Well-Architected resources and is available on the AWS Whitepaper portal.

💳 Amazon Bedrock AgentCore now offers a preview of AgentCore payments, enabling AI agents to autonomously discover and pay for APIs, MCP servers, web content, and other agents. Built with Coinbase and Stripe, the feature manages wallet authentication, x402 protocol negotiation, stablecoin payment execution, and proof delivery without interrupting an agent's reasoning loop. Developers can attach a Coinbase CDP or Stripe Privy wallet, set session-level spending limits enforced at the infrastructure layer, and observe every transaction through AgentCore's existing logs, metrics, and traces. The Coinbase x402 Bazaar MCP server is accessible via AgentCore Gateway, and the preview is available in four AWS Regions.

🔌 Amazon announced that Bedrock AgentCore Runtime now supports bring-your-own file system mounts for Amazon S3 Files and Amazon EFS access points. Developers can attach these file systems into every agent session at a specified path so agents use standard file operations without custom mount code, privileged containers, or pre-run download orchestration. The feature preserves sub-millisecond latency for active data and NFS close-to-open consistency. It is available across the 15 AWS Regions that support AgentCore Runtime and requires an access point ARN plus a configured VPC.

🧠 Amazon Bedrock AgentCore Memory now supports metadata on long-term memory (LTM) records, enabling agents to tag, filter, and retrieve memories using structured attributes alongside semantic search. You can define up to ten indexed keys per memory resource with STRING, NUMBER, and STRING_LIST types and apply operator filters to refine retrieval results. Metadata can be attached at ingestion or inferred automatically by the LLM using extraction instructions defined on the memory resource. This capability is available today in all AWS Regions where AgentCore Memory is supported.

🔒 Amazon announces that Bedrock AgentCore is now available in the AWS GovCloud (US-West) Region, bringing enterprise-grade agentic AI to workloads with elevated compliance and data residency requirements. AgentCore is a managed platform for building, deploying, and operating AI agents at scale without customers managing infrastructure. Core capabilities include AgentCore Runtime for session-isolated, long-running agents; AgentCore Gateway, which uses the Model Context Protocol to convert APIs and Lambda functions into agent-ready tools with controlled access to enterprise services; AgentCore Identity for integrated authentication and permission delegation; and AgentCore Observability and Evaluations for real-time monitoring and continuous quality assessment in production.

🔒 Amazon announced AgentCore availability in the AWS GovCloud (US-West) region, bringing enterprise-grade agent capabilities to workloads with elevated compliance needs. AgentCore is a managed platform for building, deploying, and operating AI agents at scale without customers managing infrastructure. Its composable services—including Runtime, Gateway, Identity, Observability, and Evaluations—enable session isolation, long-running workloads, secure access to enterprise data via the Model Context Protocol, and integration with existing identity providers.

🚀 Amazon Bedrock AgentCore is now available in the AWS South America (São Paulo) Region. AgentCore provides a platform to build, connect, and optimize agents with runtime, identity, gateway, policy, observability, code interpreter, and browser tools available at launch. Customers can deploy agents closer to end users to reduce latency and meet data residency requirements, with security enforced at the infrastructure layer that agents cannot bypass.

🔐 Amazon Bedrock AgentCore Identity now supports On-Behalf-Of (OBO) token exchange, enabling developers to build agents that securely access protected resources on behalf of authenticated users without additional consent flows. The OBO exchange issues a new, scoped-down access token that carries both the user and agent identities, granting just-in-time, least-privilege access to outbound services. This capability is generally available in 14 AWS Regions.

🔧 Amazon announced a preview of optimization features for Bedrock AgentCore, adding automated recommendations plus batch evaluations and controlled A/B tests. These capabilities complete the observe–evaluate–improve loop by converting evaluation outputs and production traces into suggested system prompts and refined tool descriptions tailored to specific workloads. Batch evaluations validate recommendations against predefined test cases, while A/B tests measure impact on held-out or live traffic with statistical significance before changes are promoted and only after user approval.

🧩 Amazon Quick has introduced preview Microsoft 365 extensions for Excel, PowerPoint, and Word that let the service perform tasks directly inside users’ Microsoft 365 environments. The Excel extension supports complex spreadsheet analysis including pivot tables, charts, and data import/cleaning. PowerPoint enables template-driven deck creation and refinement from Quick data, while Word gains formatted document generation, sweeping edits with track changes, and reviewer participation in comments. The extensions are available in multiple AWS regions for early access.

🛡️ This article outlines AWS guidance for integrating trust, safety, and responsible-AI practices into applications built on Amazon Bedrock. It defines core responsible AI dimensions—such as safety, controllability, fairness, explainability, security and privacy, robustness, governance, and transparency—and maps them to lifecycle stages: design, deployment, and operations. It recommends observability and guardrail tools like Amazon CloudWatch and Bedrock Guardrails for monitoring, abuse detection, configurable content filters, and hallucination controls, and describes an abuse response process for coordination with AWS Trust & Safety.

🚀 Amazon Bedrock now includes OpenAI GPT OSS (120B and 20B) and NVIDIA Nemotron models (Nano 9B v2, Nano 12B v2, Nano 30B, Super 120B), enabling developers to access open-weight foundation models through a single API. The integration is powered by Mantle, a distributed inference engine that provides serverless, high-performance inference, unified capacity pools, automated quota management, and OpenAI API compatibility. These models are available on AWS GovCloud (US) for compliant, enterprise-grade deployments.

🚀 Amazon announced that Amazon Bedrock now provides access to the latest OpenAI models, Codex, and a Managed Agents offering in limited preview. OpenAI models and Codex integrate with Bedrock controls such as IAM, AWS PrivateLink, encryption, and CloudTrail, and usage can be applied toward existing AWS cloud commitments. Managed Agents run on Bedrock AgentCore, log actions per agent, and keep inference within the customer's AWS environment.

🔒 AWS has announced general availability of the AWS for SAP MCP Server on Amazon Bedrock AgentCore, enabling AI agents to connect directly and securely to SAP ERP systems at scale. Built on Model Context Protocol (MCP) and SAP OData standards, the server supports CRUD access to sales orders, purchase orders, materials, and finance documents. The managed AgentCore Runtime provides session isolation, private connectivity, and dual-layer authentication with CloudWatch telemetry and CloudFormation templates for rapid, no-infrastructure deployment.

🔍 AWS has extended Elastic Beanstalk's AI-powered environment analysis to Windows Server platforms, enabling developers and operators to diagnose and resolve Windows-based environment issues more quickly. The feature collects recent events, instance health metrics, and logs from Windows instances and sends that telemetry to Amazon Bedrock for analysis. You can request an AI analysis from the Elastic Beanstalk console using the AI Analysis button or programmatically via the AWS CLI with the RequestEnvironmentInfo and RetrieveEnvironmentInfo operations. Results include step-by-step troubleshooting recommendations tailored to the environment's current state and are available in Regions where both services are offered.