Artificial Intelligence
Category: Amazon Bedrock Agents
Building a voice-driven AWS assistant with Amazon Nova Sonic
In this post, we explore how to build a sophisticated voice-powered AWS operations assistant using Amazon Nova Sonic for speech processing and Strands Agents for multi-agent orchestration. This solution demonstrates how natural language voice interactions can transform cloud operations, making AWS services more accessible and operations more efficient.
Amazon Bedrock AgentCore Observability with Langfuse
In this post, we explain how to integrate Langfuse observability with Amazon Bedrock AgentCore to gain deep visibility into an AI agent’s performance, debug issues faster, and optimize costs. We walk through a complete implementation using Strands agents deployed on AgentCore Runtime followed by step-by-step code examples.
Accelerating genomics variant interpretation with AWS HealthOmics and Amazon Bedrock AgentCore
In this blog post, we show you how agentic workflows can accelerate the processing and interpretation of genomics pipelines at scale with a natural language interface. We demonstrate a comprehensive genomic variant interpreter agent that combines automated data processing with intelligent analysis to address the entire workflow from raw VCF file ingestion to conversational query interfaces.
Build a device management agent with Amazon Bedrock AgentCore
In this post, we explore how to build a conversational device management system using Amazon Bedrock AgentCore. With this solution, users can manage their IoT devices through natural language, using a UI for tasks like checking device status, configuring WiFi networks, and monitoring user activity.
Secure ingress connectivity to Amazon Bedrock AgentCore Gateway using interface VPC endpoints
In this post, we demonstrate how to access AgentCore Gateway through a VPC interface endpoint from an Amazon Elastic Compute Cloud (Amazon EC2) instance in a VPC. We also show how to configure your VPC endpoint policy to provide secure access to the AgentCore Gateway while maintaining the principle of least privilege access.
Build multi-agent site reliability engineering assistants with Amazon Bedrock AgentCore
In this post, we demonstrate how to build a multi-agent SRE assistant using Amazon Bedrock AgentCore, LangGraph, and the Model Context Protocol (MCP). This system deploys specialized AI agents that collaborate to provide the deep, contextual intelligence that modern SRE teams need for effective incident response and infrastructure management.
Running deep research AI agents on Amazon Bedrock AgentCore
AI agents are evolving beyond basic single-task helpers into more powerful systems that can plan, critique, and collaborate with other agents to solve complex problems. Deep Agents—a recently introduced framework built on LangGraph—bring these capabilities to life, enabling multi-agent workflows that mirror real-world team dynamics. The challenge, however, is not just building such agents but […]
How Skello uses Amazon Bedrock to query data in a multi-tenant environment while keeping logical boundaries
Skello is a leading human resources (HR) software as a service (SaaS) solution focusing on employee scheduling and workforce management. Catering to diverse sectors such as hospitality, retail, healthcare, construction, and industry, Skello offers features including schedule creation, time tracking, and payroll preparation. We dive deep into the challenges of implementing large language models (LLMs) for data querying, particularly in the context of a French company operating under the General Data Protection Regulation (GDPR).
Skai uses Amazon Bedrock Agents to significantly improve customer insights by revolutionized data access and analysis
Skai (formerly Kenshoo) is an AI-driven omnichannel advertising and analytics platform designed for brands and agencies to plan, launch, optimize, and measure paid media across search, social, retail media marketplaces and other “walled-garden” channels from a single interface. In this post, we share how Skai used Amazon Bedrock Agents to improve data access and analysis and improve customer insights.
Enhancing LLM accuracy with Coveo Passage Retrieval on Amazon Bedrock
In this post, we show how to deploy Coveo’s Passage Retrieval API as an Amazon Bedrock Agents action group to enhance response accuracy, so Coveo users can use their current index to rapidly deploy new generative experiences across their organization.









