Amazon Bedrock Agents is AWS's fully managed service for building autonomous AI agents capable of multi-step reasoning, knowledge retrieval, and API execution. Released in GA in late 2023 as part of the broader Amazon Bedrock platform, Bedrock Agents provides the orchestration layer that turns foundation models into agents that can take action — browsing knowledge bases, calling APIs, returning structured responses, and breaking complex tasks into subtasks.
For organizations already committed to AWS, Bedrock Agents offers a compelling value proposition: agent infrastructure without the operational overhead of managing agent frameworks, vector databases, and API orchestration layers. It integrates natively with S3, Lambda, OpenSearch, DynamoDB, and the full suite of AWS services.
Key Features#
Multi-Model Access Bedrock Agents works with the full catalog of foundation models available in Amazon Bedrock: Anthropic Claude (3.5 Sonnet, 3 Opus, 3 Haiku), Meta Llama 3, Amazon Titan, Mistral, and others. This model variety within a single platform allows teams to choose models by capability, cost, and latency for different agent applications.
Knowledge Bases Integration Bedrock Agents connects to Bedrock Knowledge Bases — managed RAG infrastructure that indexes documents from S3 into a vector store (Amazon OpenSearch Serverless or Pinecone). Agents query these knowledge bases automatically when answering questions, enabling document-grounded responses without custom RAG pipeline engineering.
Action Groups (API Orchestration) Action groups define what an agent can do. You provide an OpenAPI schema describing API endpoints, and Bedrock Agents automatically calls the appropriate Lambda function when the agent determines an action is needed. This serverless function pattern integrates cleanly with existing AWS backends.
Return of Control Bedrock Agents' "return of control" feature allows the agent to pause execution and return a structured result to the calling application, which then decides the next step. This human-in-the-loop pattern is essential for enterprise applications where autonomous action requires human confirmation for high-stakes operations.
Session Management Bedrock Agents maintains conversation context across multi-turn sessions. Session attributes allow you to pass user-specific context (authentication data, preferences, session metadata) that persists throughout an agent interaction.
Inline Agents (Beta) A newer capability allowing dynamic agent configuration at runtime — changing instructions, knowledge bases, and action groups on a per-session basis. This enables personalization and multi-tenant agent deployments from a single configuration.
Pricing#
Amazon Bedrock Agents charges based on:
- Model inference: Billed per input/output token at standard Bedrock model rates (e.g., Claude 3.5 Sonnet: ~$3/million input tokens, ~$15/million output tokens as of early 2026; verify current rates at aws.amazon.com/bedrock/pricing)
- Knowledge Base queries: Per query charge for OpenSearch Serverless (~$0.00025/query) plus vector store hosting costs
- No separate Agents service fee: Orchestration is included in the model inference pricing
A typical production agent handling 10,000 user requests/day with Claude 3 Haiku might cost $50–200/day depending on conversation length. Model selection is the primary cost lever.
Who It's For#
Amazon Bedrock Agents is the right choice for:
- AWS-native organizations building production AI applications within the AWS ecosystem
- Enterprise engineering teams that need agent capabilities without managing agent orchestration infrastructure
- Applications requiring AWS compliance certifications (SOC 2, HIPAA, PCI DSS) that Bedrock inherits from AWS
- Teams building multi-agent systems using Bedrock's supervisor and subagent patterns for complex task decomposition
It is less suitable for organizations on GCP or Azure (use Vertex AI Agents or Azure AI Agents instead), for teams needing model providers not available on Bedrock, or for applications requiring the maximum customization of open-source frameworks.
Strengths#
AWS ecosystem integration. The depth of integration with S3, Lambda, DynamoDB, OpenSearch, CloudWatch, and IAM is unmatched for AWS-native deployments. Agents can interact with essentially any AWS service via Lambda action groups.
No infrastructure management. AWS handles scaling, availability, and the orchestration runtime. Teams don't manage agent servers, vector database infrastructure, or orchestration middleware — just their business logic in Lambda functions.
Enterprise compliance. Bedrock inherits AWS's comprehensive compliance certifications across healthcare, financial services, government, and other regulated industries. For compliance-sensitive deployments, this is a significant overhead reduction.
Multi-model flexibility. Access to Anthropic, Meta, Amazon, and Mistral models within a single platform gives teams options without managing multiple vendor relationships and APIs.
Limitations#
AWS lock-in. Bedrock Agents applications are tightly coupled to AWS infrastructure. Migrating to a different cloud or self-hosted infrastructure requires significant rework.
Less flexible than open-source frameworks. The managed service model constrains what's possible. Teams needing custom agent loop logic, unusual memory patterns, or non-standard tool execution will find the AWS-managed model limits their options.
Cost complexity. The intersection of model pricing, knowledge base costs, Lambda execution, and OpenSearch hosting makes total cost estimation non-trivial for complex deployments. Unexpected costs from misconfigured knowledge base queries have caught teams off guard.
Related Resources#
Browse the full AI Agent Tools Directory for managed and cloud-native agent platform options.
Related profiles: Google Vertex AI Agents and Microsoft Copilot Studio for hyperscaler alternatives.
Comparisons: Amazon Bedrock Agents vs Google Vertex AI Agents and AWS Bedrock vs Azure AI Foundry: Enterprise AI Platform Comparison.
For implementation guides, see Building Production RAG Applications on Amazon Bedrock and AWS AI Agent Architecture Patterns.