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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Companies of all sizes face mounting pressure to operate efficiently as they manage growing volumes of data, systems, and customer interactions. The chat agent bridges complex information systems and user-friendly communication. Then the user interacts with the chat application using natural language.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. This post guides you through implementing a queue management system that automatically monitors available job slots and submits new jobs as slots become available.

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Creating asynchronous AI agents with Amazon Bedrock

AWS Machine Learning - AI

This post will discuss agentic AI driven architecture and ways of implementing. Alternatively, asynchronous choreography follows an event-driven pattern where agents operate autonomously, triggered by events or state changes in the system.

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How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock

AWS Machine Learning - AI

In this collaboration, the Generative AI Innovation Center team created an accurate and cost-efficient generative AIbased solution using batch inference in Amazon Bedrock , helping GoDaddy improve their existing product categorization system. The security measures are inherently integrated into the AWS services employed in this architecture.

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Harness the power of MCP servers with Amazon Bedrock Agents

AWS Machine Learning - AI

AI agents extend large language models (LLMs) by interacting with external systems, executing complex workflows, and maintaining contextual awareness across operations. Through this architecture, MCP enables users to build more powerful, context-aware AI agents that can seamlessly access the information and tools they need.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

We walk through the key components and services needed to build the end-to-end architecture, offering example code snippets and explanations for each critical element that help achieve the core functionality. You can invoke Lambda functions from over 200 AWS services and software-as-a-service (SaaS) applications.

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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

Solution overview This section outlines the architecture designed for an email support system using generative AI. High Level System Design The solution consists of the following components: Email service – This component manages incoming and outgoing customer emails, serving as the primary interface for email communications.