I will review the Best Managed Agent Orchestration Platforms on AWS. I will cover how these platforms improve automated workflows with Amazon Web Services (AWS), increase the durability of artificial intelligence (AI) agents, and enhance governance.
The platforms I review will be AWS Bedrock Agents and AWS Step Functions and other competing multi-cloud offerings, Temporal and LangGraph. I will consider the features and prices of each offering to evaluate their use cases in enterprises that primarily rely on AWS and in enterprises that rely on other cloud offerings.
What Are Managed Agent Orchestration Platforms?
An Managed Agent Orchestration Platform is a service that helps users to manage and scale a large number of AI agents or workflows across public clouds (e.g. AWS). Such a platform provides customers with a setting in which AI agents can work together, and also helps to manage failure and recover it.
It usually provides integration with some AWS services (e.g. Lambda, S3 and DynamoDB), and consequently enables users to run enterprise workloads. Its charging mechanism is also flexible, and it is either charging per use (or hour), or charges a subscription fee.
From the perspective of deployment, it provides a fully managed service. In addition, it offers either a hybrid, or an entirely free and open source, framework, to customers. Overall, it helps companies to have its agents ecosystems, and at the same time control its environment.
Quick Comparison Table
| Platform | Category | Best For | Hosting | Pricing Model |
|---|---|---|---|---|
| AWS Bedrock Agents | Cloud-native | Enterprise AI agents on AWS | AWS SaaS | Usage-based |
| AWS Step Functions | Workflow orchestration | Durable serverless orchestration | AWS SaaS | Pay-per-state transition |
| LangGraph | Developer framework | Complex multi-agent workflows | Open source + managed | Free core; usage-based |
| Temporal | Durable runtime | Long-running workflows | Cloud SaaS + OSS | Free OSS; SaaS subscription |
| Restate | Durable execution | Replayable agent workflows | SaaS | Usage-based |
| Inngest | Event orchestration | Replayable serverless steps | SaaS | Usage-based |
| CrewAI | Developer framework | Role-based agent teams | OSS + enterprise | Free core; enterprise quote |
| OpenAI Agents SDK | SDK framework | GPT-native orchestration | OSS SDK | Free SDK; API usage fees |
| UiPath Agentic Automation | Enterprise automation | Human-in-the-loop orchestration | SaaS + on-prem | Subscription |
| Gemini Enterprise Agent Platform | Cloud enterprise | Governance + scaling | Google Cloud SaaS | Usage-based |
1. AWS Bedrock Agents
AWS Bedrock Agents was founded in 2023 as part of Amazon’s Bedrock suite to simplify development of generative AI agents. With native integration to AWS services, Bedrock Agents facilitates seamless orchestration across various enterprise workloads and supports integrated AI agents.

As part of Amazon’s Bedrock suite, Bedrock Agents follows a usage model where customers incur charges based on the number of API calls and agent executions. From a deployment standpoint, Bedrock Agents are offered as a fully managed service. From an enterprise customers’ perspective, Bedrock Agents offer a means to execute and orchestrate various AI agents within the AWS ecosystem.
Agent Team Architecture: Employs a centralized approach to orchestration. Integrates AWS specific connectors.
Best-Fit Users: Large companies which have standardized or are in the process of standardizing their cloud infrastructure on AWS.
Limitations: Lock-in to AWS.
Strengths: Easy integration with various AWS services.
Example of Use Case: Enterprises wish to orchestrate AI agents and workers which require compliance.
| Feature | Details |
|---|---|
| Founded | 2023 |
| AWS Integration | Native with Lambda, DynamoDB, S3 |
| Pricing | Usage-based (per API call) |
| Deployment | Fully managed SaaS |
| Governance | Enterprise-grade monitoring & compliance |
| Scalability | Auto-scaling across AWS workloads |
| Security | Integrated IAM & encryption |
| Target Users | Enterprises standardizing on AWS |
| Strength | Simplifies generative AI agent orchestration |
2. AWS Step Functions
Launched in 2016, AWS Step Functions enable customers to build and execute sophisticated workflows with AI-based software agents. It offers integrations with AWS services and Bedrock Agents to provide advanced workflow orchestration with retries and recovery from errors.

It can be an affordable solution for workflows with predictable, simple structures, as it charges per state transition. Similar to other AWS services, Step Functions are offered as SaaS solutions, removing the need for customers to manage any infrastructure. It is primarily aimed at customers that need to implement long-running workflows with thousands of interacting software agents, while adhering to internal compliance requirements.
Agent Team Architecture: Orchestrates workflows using state machines.
Best-Fit Users: Enterprises.
Limitations: Costs associated with state transitions.
Strengths: Dependability and reliability for transferring and managing workload over a long duration.
Example of Use Case: Serverless or disruptive architectural style for orchestrating and integrating AI and ML services.
| Feature | Details |
|---|---|
| Founded | 2016 |
| AWS Integration | Deep with Lambda, ECS, Bedrock |
| Pricing | Pay-per-state transition |
| Deployment | AWS-native SaaS |
| Durability | Checkpoints & retries |
| Workflow Type | Long-running orchestration |
| Security | IAM-based access |
| Target Users | Enterprises needing durable workflows |
| Strength | Proven orchestration reliability |
3. LangGraph
LangGraph is an open source framework for multi-agent orchestration developed in 2024. Through AWS SDKs and cloud connectors, agents can be deployed on AWS Lambda or ECS. LangGraph offers a free core edition and charges for an enterprise version.

The core edition offers a SaaS model. There is a choice of hybrid deployment, with developers being able to host LangGraph themselves. LangGraph is powerful in complex multi agent scenario’s. Users can build end to end solutions using LangGraph and AWS.
Agent Team Architecture: Supports collaboration between heterogeneous agents.
Best-Fit Users: Startups and software development companies.
Limitations: Requires customization and implementation by engineers.
Strengths: Open source.
Example of Use Case: Advanced and intricate agent orchestration and collaboration on AWS.
| Feature | Details |
|---|---|
| Founded | 2024 |
| AWS Integration | SDKs & connectors |
| Pricing | Free core; usage-based SaaS |
| Deployment | Hybrid (self-hosted + cloud) |
| Workflow Type | Multi-agent orchestration |
| Flexibility | Customizable workflows |
| Target Users | Developers & startups |
| Strength | Complex agent collaboration |
| Governance | Optional enterprise support |
4. Temporal
Founded in 2020, Temporal also provides a durable workflow engine. Similar to LangGraph, Temporal has a hybrid model, meaning the customer can self-host or use Temporal’s cloud product. Temporal integrates easily with other AWS products and services, and gives customers a way to build and run workflows using the Temporal engine on AWS.

Like LangGraph, the Temporal engine is free for the core product, and a managed, SaaS product is available for an enterprise offering. Due to its durability, Temporal is commonly used to build intelligent workflows for AI and other automation agents in the Enterprise.
Agent Team Architecture: Reliable and fault tolerant orchestration for workflows.
Best-Fit Users: Enterprises.
Limitations: Difficulty in self-hosting due to lack of cluster management.
Strengths: Persistence for long lasting workflows.
Example of Use Case: Mission Critical and High Availability workload orchestration and management.
| Feature | Details |
|---|---|
| Founded | 2020 |
| AWS Integration | EC2, Kubernetes connectors |
| Pricing | Free OSS; SaaS subscription |
| Deployment | Hybrid (self-hosted + cloud) |
| Durability | Long-running workflow persistence |
| Workflow Type | Stateful orchestration |
| Target Users | Enterprises needing reliability |
| Strength | Fault-tolerant execution |
| Governance | Enterprise-grade audit logs |
5. Restate
Founded in 2023, Restate also offers a SaaS product for building and orchestrating AI workflows. Restate’s product integrates with other AWS services like Lambda and API gateway. Similar to LangGraph, Restate’s product is powerful for certain types of stateful workflows, and therefore agents, in the serverless environment.

Restate charges based on usage, and offers a free tier for individual developers. Lastly, building on the other products reviewed, Inngest also offers a SaaS product for integrating serverless architectures, and charges based on usage.
Agent Team Architecture: Provides state recovery and workflow replay.
Best-Fit Users: Enterprises.
Limitations: SaaS only.
Strengths: State recovery and workflow replay.
Example of Use Case: Orchestrating workflows for Lambda functions.
| Feature | Details |
|---|---|
| Founded | 2023 |
| AWS Integration | Lambda & API Gateway |
| Pricing | Usage-based SaaS |
| Deployment | Fully managed SaaS |
| Durability | Replayable workflows |
| Workflow Type | Stateful orchestration |
| Target Users | Enterprises needing resilience |
| Strength | Recovery from interruptions |
| Governance | Built-in monitoring |
6. Inngest
Inngest is an event-driven orchestration service built for serverless environments, launched in 2022. As of now, it connects with AWS services: Lambda, SQS, and Event Bridge. As such, it is well positioned to power event based agent workflows in AWS.

It provides a free tier for developers and charges a usage based rate for Enterprise customers. It is available as SaaS and as a download for self-hosting. It focuses on providing workflows that are replayable. This provides the ability to debug and re-run workflows. This is very relevant for AWS orchestration.
Agent Team Architecture: Employs replayable steps for workflow orchestration.
Best-Fit Users: Enterprises.
Limitations: SaaS only.
Strengths: State recovery and workflow replay.
Example of Use Case: Workflows for integrating AI services.
| Feature | Details |
|---|---|
| Founded | 2022 |
| AWS Integration | Lambda, SQS, EventBridge |
| Pricing | Usage-based; free tier |
| Deployment | SaaS + optional self-host |
| Workflow Type | Event-driven orchestration |
| Durability | Replayable workflows |
| Target Users | Developers & enterprises |
| Strength | Debugging & re-run support |
| Governance | Cloud monitoring tools |
7. CrewAI
Established in 2024, CrewAI provides enterprises with a multi-agent orchestration framework. CrewAI leverages containers to provide agent team capabilities on Amazon ECS and Kubernetes. Agent teams can be developed using a freemium model.

Enterprise specific support is offered by CrewAI. Self-hosted and managed deployments are offered by CrewAI. Organizations that require development of large-scale agent ecosystems using AWS can use CrewAI.
Agent Team Architecture: Role-based agent teams with defined responsibilities.
Best-Fit Users: Developer teams building collaborative agents.
Limitations: Requires manual role definition and setup.
Strength: Flexible agent collaboration ecosystems.
Use Case: Multi-agent orchestration with role specialization.
| Feature | Details |
|---|---|
| Founded | 2024 |
| AWS Integration | ECS, Kubernetes |
| Pricing | Free OSS; enterprise support |
| Deployment | Hybrid (self-hosted + enterprise) |
| Workflow Type | Role-based multi-agent |
| Flexibility | Custom agent roles |
| Target Users | Developer teams |
| Strength | Agent collaboration ecosystems |
| Governance | Enterprise-grade support available |
8. OpenAI Agents SDK
In 2025, OpenAI launched their Agents SDK. This software allowed developers to generate GPT-based agents. Initially, the SDK allowed developer-managed connection and orchestration of GPT agents over the AWS cloud using Lambda functions and API connectors.

The SDK is free; however, OpenAI’s API calls carry a cost. Agents are deployed and managed by developers using AWS or OpenAI’s cloud. Using the SDK, developers can utilize GPT agents over AWS and gain benefits of scalability. The SDK gives developers control over agent management and orchestration.
Agent Team Architecture: GPT-native orchestration toolkit.
Best-Fit Users: Developers building GPT-powered agents.
Limitations: Dependent on OpenAI API usage costs.
Strength: Fine-grained orchestration of GPT agents.
Use Case: AI-driven orchestration integrated with AWS Lambda.
| Feature | Details |
|---|---|
| Founded | 2025 |
| AWS Integration | APIs & Lambda |
| Pricing | Free SDK; API usage fees |
| Deployment | Developer-centric |
| Workflow Type | GPT-native orchestration |
| Flexibility | Fine-grained agent control |
| Target Users | Developers building GPT agents |
| Strength | GPT orchestration in AWS |
| Governance | API-based monitoring |
9. UiPath Agentic Automation
The UiPath agent automation platform was originally released in 2005. It expanded to include agent orchestration in 2024. UiPath integrates with AWS via APIs and cloud connectors. UiPath employs a subscription model for licensing. Licenses are sold via enterprise models. UiPath automation suits can be deployed via the SaaS or on-prem model.

This gives customers flexibility. UiPath differentiates from competitors by allowing workflow approval checkpoints via human interaction. UiPath helps customers with compliance obligations. UiPath integrates well with AWS services and provides advanced automation features with audit capabilities for customers of AWS.
Agent Team Architecture: Human-in-the-loop orchestration with compliance checkpoints.
Best-Fit Users: Regulated industries needing governance.
Limitations: Subscription costs can be high.
Strength: Strong compliance and audit trails.
Use Case: Enterprise automation with AWS integration.
| Feature | Details |
|---|---|
| Founded | 2005 (expanded 2024) |
| AWS Integration | Cloud connectors & APIs |
| Pricing | Subscription-based enterprise licensing |
| Deployment | SaaS + on-prem |
| Workflow Type | Human-in-the-loop orchestration |
| Governance | Strong compliance & audit trails |
| Target Users | Regulated industries |
| Strength | Approval checkpoints |
| Security | Enterprise-grade identity management |
10. Gemini Enterprise Agent Platform
The Gemini Enterprise Agent Platform (by Google Cloud) and AWS Bedrock were launched in 2025. Gemini leverages AWS connectors and provides multi-cloud orchestration with Google Cloud. Like Bedrock, Gemini uses usage-based pricing.

Gemini provides more advanced controls for governance, compliance, and multi-cloud orchestration. Gemini is more beneficial to customers who need to orchestrate workloads across multiple clouds. For users tied to the AWS environment, Bedrock would be the better choice.
Agent Team Architecture: Multi-cloud orchestration with enterprise governance.
Best-Fit Users: Enterprises operating across AWS and Google Cloud.
Limitations: Less AWS-native compared to Bedrock.
Strength: Advanced monitoring and compliance features.
Use Case: Multi-cloud orchestration at enterprise scale.
| Feature | Details |
|---|---|
| Founded | 2025 (Google Cloud) |
| AWS Integration | Multi-cloud connectors |
| Pricing | Usage-based SaaS |
| Deployment | Fully managed SaaS |
| Workflow Type | Enterprise-scale orchestration |
| Governance | Advanced monitoring & compliance |
| Target Users | Multi-cloud enterprises |
| Strength | Competes with AWS Bedrock |
| Security | Cloud-native identity management |
How To Choose Managed Agent Orchestration Platforms for AWS
Integration Depth: Look for platform integration with AWS services like Lambda, DynamoDB, S3, and others.
Durability and Reliability: Look for support for at large workflows and state persistence.
Governance and Compliance: Look for support for auditing and identification and integration with compliance services.
Pricing Model: Look for both, subscription and usage models.
Deployment Model: Look for SaaS models (e.g., Bedrock, UiPath), and hybrid models (e.g., Temporal and LangGraph) and support frameworks (CrewAI).
Scaling: Look for support for large agent cluster.
Customization: Look for support for frameworks and services (Temporal, CrewAI and LangGraph) and SaaS models (Uipath and Bedrock).
Multi-cloud: Look for models like Temporal and Gemini for support across AWS and other cloud providers.
Best Users: Enterprise companies with primary business on AWS should look at Bedrock in conjunction with AWS Step Functions. Others should look at LangGraph or CrewAI.
Conclusion
There is a wide range of options for agent orchestration on AWS. Some solutions stay within the AWS environment, while others provide a multi-cloud environment. Two of the offerings from AWS are integrated and governed within the AWS environment. Languages like LangGraph, Temporal, and Restate offer building blocks to design and orchestrate workflows.
For events-based orchestration, CrewAI and Inngest offer building blocks, and the OpenAI Agents SDK offers building blocks for designing workflows within AWS using GPT technology. For managing automation at the enterprise level, UiPath and Gemini offer solutions that integrate governance and control across multiple clouds. These offers provide companies a way to keep innovation and control within the environment.
FAQ
What are AWS Bedrock Agents?
AWS Bedrock Agents are a fully managed orchestration service launched in 2023, designed to simplify building and deploying generative AI agents. They integrate seamlessly with AWS services like Lambda and DynamoDB, offering usage-based pricing and a SaaS deployment model.
What is LangGraph used for?
LangGraph, founded in 2024, is an open-source framework for multi-agent orchestration. It integrates with AWS via SDKs and connectors, offering free core usage and optional managed SaaS deployment for enterprises.
Why is Temporal popular for AWS workflows?
Temporal, founded in 2020, is known for durable execution of long-running workflows. It integrates with AWS EC2 and Kubernetes, offering both free open-source and subscription-based SaaS deployment models.
What makes Restate unique?
Restate, launched in 2023, specializes in replayable agent workflows. It integrates with AWS Lambda and API Gateway, offering usage-based SaaS pricing and strong stateful orchestration capabilities.
How does Inngest work with AWS?
Inngest, founded in 2022, is an event-driven orchestration platform. It integrates with AWS services like Lambda and EventBridge, offering replayable workflows with a SaaS deployment model and usage-based pricing.

