Category: Technical How-to

In this post, we introduce the Multi-Provider Generative AI Gateway reference architecture, which provides guidance for deploying LiteLLM into an AWS environment to streamline the management and governance of production generative AI workloads across multiple model providers. This centralized gateway solution addresses common enterprise challenges including provider fragmentation, decentralized governance, operational complexity, and cost management by offering a unified interface that supports Amazon Bedrock, Amazon SageMaker AI, and external providers while maintaining comprehensive security, monitoring, and control capabilities.

In this post, we explore deployment patterns and best practices for Claude Code with Amazon Bedrock, covering authentication methods, infrastructure decisions, and monitoring strategies to help enterprises deploy securely at scale. We recommend using Direct IdP integration for authentication, a dedicated AWS account for infrastructure, and OpenTelemetry with CloudWatch dashboards for comprehensive monitoring to ensure secure access, capacity management, and visibility into costs and developer productivity .

Amazon Bedrock Guardrails now extends its safety controls to protect code generation across twelve programming languages, addressing critical security challenges in AI-assisted software development. In this post, we explore how to configure content filters, prompt attack detection, denied topics, and sensitive information filters to safeguard against threats like prompt injection, data exfiltration, and malicious code generation while maintaining developer productivity .

In this post, we cover how you can use tools from Snowflake AI Data Cloud and Amazon Web Services (AWS) to build generative AI solutions that organizations can use to make data-driven decisions, increase operational efficiency, and ultimately gain a competitive edge.

RoboTic-Tac-Toe is an interactive game where two physical robots move around a tic-tac-toe board, with both the gameplay and robots’ movements orchestrated by LLMs. Players can control the robots using natural language commands, directing them to place their markers on the game board. In this post, we explore the architecture and prompt engineering techniques used to reason about a tic-tac-toe game and decide the next best game strategy and movement plan for the current player.

This blog post introduces two major enhancements to Amazon SageMaker HyperPod that strengthen security and storage capabilities for large-scale machine learning infrastructure. The new features include customer managed key (CMK) support for encrypting EBS volumes with organization-controlled encryption keys, and Amazon EBS CSI driver integration that enables dynamic storage management for Kubernetes volumes in AI workloads.

In this post, we demonstrate how to build a production-ready biomedical research agent by integrating Biomni’s specialized tools with Amazon Bedrock AgentCore Gateway, enabling researchers to access over 30 biomedical databases through a secure, scalable infrastructure. The implementation showcases how to transform research prototypes into enterprise-grade systems with persistent memory, semantic tool discovery, and comprehensive observability for scientific reproducibility .

Graphical user interfaces have carried the torch for decades, but today’s users increasingly expect to talk to their applications. In this post we show how we added a true voice-first experience to a reference application—the Smart Todo App—turning routine task management into a fluid, hands-free conversation.

The Cohere Embed 4 multimodal embeddings model is now available as a fully managed, serverless option in Amazon Bedrock. In this post, we dive into the benefits and unique capabilities of Embed 4 for enterprise search use cases. We’ll show you how to quickly get started using Embed 4 on Amazon Bedrock, taking advantage of integrations with Strands Agents, S3 Vectors, and Amazon Bedrock AgentCore to build powerful agentic retrieval-augmented generation (RAG) workflows.

In this post, we explore four key collaboration patterns for multi-agent, multimodal AI systems – Agents as Tools, Swarms Agents, Agent Graphs, and Agent Workflows – and discuss when and how to apply each using the open-source AWS Strands Agents SDK with Amazon Nova models.