Category: Amazon Bedrock

Amazon Bedrock now offers OpenAI GPT-5.6 models (Sol, Terra, and Luna) in more than 25 AWS Regions with cross-Region inference. Learn how US geographic and global inference profiles route requests for higher throughput, how to call the models with the OpenAI and Converse APIs, and how to configure IAM, quotas, and monitoring.

AI agents can take actions that do not match your organization’s policies. Policy in Amazon Bedrock AgentCore lets teams enforce controls across agents, now including time-based constraints. This post shows how Policy Authoring turns natural-language policy documents into correct Dogwood policies, with worked examples and best practices.

Scaling agentic AI across an enterprise requires patterns that preserve flexibility while avoiding vendor lock-in. In this second post of our multi-agent series, we examine how ML teams operate many agentic AI systems across a multi-everything environment of frameworks, models, and providers, and the principles that let those systems scale together.

Learn how AWS Professional Services uses a multi-agent framework built on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Purpose-built AI agents handle discovery, infrastructure as code generation, portfolio governance, and post-migration operations, reducing IaC development time from weeks to minutes.

Learn how to add context-aware security monitoring to FHIR APIs using Amazon Bedrock. This post shows how to detect anomalous access patterns, classify data sensitivity automatically, and generate compliance reports in natural language, all without adding latency to clinical workflows.

Web Search on Amazon Bedrock AgentCore now supports runtime domain and published-date filtering. New per-request filters give developers per-call control over which web sources their agents consult and how fresh those sources must be, all enforced server-side. This release also expands Web Search to the Europe (Ireland) and Asia Pacific (Tokyo) Regions.

In this post, you learn three serverless patterns (task-token callback, direct service integration, and durable functions) for invoking Amazon Bedrock AgentCore agents asynchronously from AWS Step Functions pipelines, eliminating idle compute costs while your AI agent processes requests.

Fanatics Betting and Gaming built a multi-agent customer support system on AWS to handle the complexity of sports betting: state-specific rules, real-time responsible gaming, and traffic spikes during major sporting events. This post walks through the architecture, the AWS services involved, and the patterns for your own multi-agent support solution.

KnowledgeForge mines resolved ITSM incident tickets into new knowledge base articles and automatically curates the existing library by deduplicating, quality-scoring, and improving content, using Amazon Bedrock, Amazon S3 Vectors, and AWS Step Functions in a multi-tenant, closed-loop pipeline.

Amazon Bedrock AgentCore payments is now generally available, enabling AI agents to autonomously transact at scale with built-in spending guardrails, protocol-agnostic payment orchestration, and production-ready observability.