Category: Amazon Bedrock Agents

In this post, we show how to extend Amazon Bedrock Agents to hybrid and edge services such as AWS Outposts and AWS Local Zones to build distributed Retrieval Augmented Generation (RAG) applications with on-premises data for improved model outcomes. With Outposts, we also cover a reference pattern for a fully local RAG application that requires both the foundation model (FM) and data sources to reside on premises.

The research team at AWS has worked extensively on building and evaluating the multi-agent collaboration (MAC) framework so customers can orchestrate multiple AI agents on Amazon Bedrock Agents. In this post, we explore the concept of multi-agent collaboration (MAC) and its benefits, as well as the key components of our MAC framework. We also go deeper into our evaluation methodology and present insights from our studies.

In this post, we propose a solution using DigitalDhan, a generative AI-based solution to automate customer onboarding and digital lending. The proposed solution uses Amazon Bedrock Agents to automate services related to KYC verification, credit and risk assessment, and notification. Financial institutions can use this solution to help automate the customer onboarding, KYC verification, credit decisioning, credit underwriting, and notification processes.

This post provides step-by-step instructions for creating a collaborative multi-agent framework with reasoning capabilities to decouple business applications from FMs. It demonstrates how to combine Amazon Bedrock Agents with open source multi-agent frameworks, enabling collaborations and reasoning among agents to dynamically execute various tasks. The exercise will guide you through the process of building a reasoning orchestration system using Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Bedrock Agents, and FMs. We also explore the integration of Amazon Bedrock Agents with open source orchestration frameworks LangGraph and CrewAI for dispatching and reasoning.

In this post, we explore how Syngenta collaborated with AWS to develop Cropwise AI, a generative AI assistant powered by Amazon Bedrock Agents that helps sales representatives make better seed product recommendations to farmers across North America. The solution transforms the seed selection process by simplifying complex data into natural conversations, providing quick access to detailed seed product information, and enabling personalized recommendations at scale through a mobile app interface.

In this post, we explore how Amazon Bedrock Agents simplify the orchestration of generative AI workflows, particularly with the introduction of the custom orchestrator feature. You can use the custom orchestrator to fine-tune and optimize agentic workflows that align more closely with specific business and operational needs. We outline the feature’s key benefits, including full control over orchestration, real-time adjustments, and reusability, followed by a breakdown of how it manages state transitions and contract-based interactions between Amazon Bedrock Agents and AWS Lambda.

For enterprises in the realm of cloud computing and software development, providing secure code repositories is essential. As sophisticated cybersecurity threats become more prevalent, organizations must adopt proactive measures to protect their assets. Amazon Bedrock offers a powerful solution by automating the process of scanning repositories for vulnerabilities and remediating them. This post explores how you can use Amazon Bedrock to enhance the security of your repositories and maintain compliance with organizational and regulatory standards.

This post demonstrates how to use Amazon Bedrock Agents, Amazon Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.

n this post, we create a virtual analyst that can answer natural language queries of stocks matching certain technical indicator criteria using Amazon Bedrock Agents.

Generative AI agents are a versatile and powerful tool for large enterprises. They can enhance operational efficiency, customer service, and decision-making while reducing costs and enabling innovation. These agents excel at automating a wide range of routine and repetitive tasks, such as data entry, customer support inquiries, and content generation. Moreover, they can orchestrate complex, […]