Amazon Bedrock Agents在 AWS 上构建并部署 AI 代理，将基础模型连接到 API 与企业数据。

4.5 (4)

审阅者 Daniel Nikulshyn·更新 2026年5月

AWS Enterprise AI Agents Managed Service RAG API Integration Foundation Models

概览

Amazon Bedrock Agents 是一项托管的 AWS 服务，用于创建能够规划、推理并执行多步任务的 AI 代理，通过将基础模型与外部 API、知识库和业务系统结合。开发者以声明式方式配置代理，Bedrock 负责编排、提示工程、记忆管理和工具的安全调用。代理能够理解自然语言用户请求，拆分为步骤，检索连接数据源的相关上下文，并调用后端服务完成诸如处理订单、查询数据库或生成报告等操作。由于在 AWS 内运行，该服务可与 IAM、CloudWatch、Lambda 等 AWS 基础设施集成，实现面向生产的安全和可观测性。

主要功能

多步任务规划与推理
API 与 Lambda 函数调用
RAG 知识库集成
会话记忆与上下文处理
选择 Bedrock 基础模型
CloudWatch 日志与追踪

价格

模型: Contact for pricing
分类: AI Agent Development Platforms
评分: 4.5 / 5 (4)

使用场景

自动化客户订单处理

构建一个能够理解自然语言客户请求、通过 Lambda 查询订单数据库并对后台 API 执行多步履行操作的代理。

企业知识助手

将 Bedrock 知识库连接到内部文档，让代理通过 RAG 检索有根基的答案并为员工生成报告。

通过聊天进行内部数据库查询

让非技术人员用自然语言提问，代理规划步骤、调用 API，并返回企业系统的结构化结果。

安全多步工作流自动化

利用 IAM 保护的工具调用、会话记忆和 CloudWatch 追踪，跨 AWS 服务编排复杂业务工作流，实现审计可追溯性。

优点 & 缺点

优点

完全托管的编排，无需维护代理基础设施
与 AWS 服务及 IAM 安全的原生集成
通过 Bedrock 支持多种基础模型
内置通过知识库检索实现答案可靠性

缺点

与 AWS 生态系统绑定
高流量工作负载的定价难以预测
对 AWS 新手团队而言学习曲线陡峭
与自定义代理框架相比灵活性有限

评测

4.5

4 个评分的平均值。

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Joanna Kowalski

Mar 18, 2026

Solid for our team

We rolled this out across the team last quarter and supports multiple foundation models through Bedrock. Multi-step task planning and reasoning fits neatly into how we already work, and session memory and context handling removed a step we used to do by hand. but it has held up under daily use.

Omar Haddad

Jan 10, 2026

Solid for our team

We rolled this out across the team last quarter and native integration with AWS services and IAM security. Choice of Bedrock foundation models fits neatly into how we already work, and session memory and context handling removed a step we used to do by hand. Steeper learning curve for teams new to AWS, which is the main caveat, but it has held up under daily use.

Beatriz Costa

Aug 2, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is session memory and context handling — handled better than most — and native integration with AWS services and IAM security. Worth the time if this is your use case.

Rina Desai

Jul 11, 2025

Solid for our team

We rolled this out across the team last quarter and native integration with AWS services and IAM security. CloudWatch logging and tracing fits neatly into how we already work, and cloudWatch logging and tracing removed a step we used to do by hand. Tied to the AWS ecosystem, which is the main caveat, but it has held up under daily use.

问答

What can I actually build with Amazon Bedrock Agents?

You can build AI agents that handle multi-step tasks like processing orders, querying databases, or generating reports. Agents interpret natural language, plan steps, pull context from Knowledge Bases via RAG, and invoke APIs or Lambda functions to complete actions.

What are the main limitations or downsides to consider?

Bedrock Agents is tied to the AWS ecosystem, so it's less portable than custom frameworks and offers less flexibility for bespoke orchestration. Pricing can be hard to predict at high volumes, and teams new to AWS may face a steeper learning curve.

How does it integrate with my existing AWS environment?

It runs natively on AWS with built-in integrations for IAM (security and permissions), Lambda (custom tool execution), CloudWatch (logging and tracing), and Bedrock Knowledge Bases for retrieval. This makes it well-suited for teams already standardized on AWS infrastructure.