The Agent Management Platform
Start automating with AI agents today
CrewAI's Agent Management Platform (AMP) empowers anyone to automate intelligence-driven, time-consuming processes and tasks by building crews of AI agents that perform them autonomously.
Why enterprises succeed with CrewAI
Easy
Build and integrate a crew of AI agents that support you in minutes via natural language, a drag-and-drop UI or intuitive code.
- CrewAI studio visual editor
- Integrated tools and triggers
- Simple yet powerful APIs
Trusted
Delegate critical tasks to agentic workflows that produce repeatable, reliable outcomes which meet expectations.
- Workflow tracing
- Agent training
- Task guardrails
Scalable
Streamline and accelerate Agent AI adoption across every business unit, department and team with centralized management and comprehensive monitoring.
- LLM and tool configuration
- Role-based access control
- Serverless containers
Agentic AI made easy, for everyone
CrewAI Studio
Build, run, trace and deploy a custom agentic workflow in minutes with natural language and a drag-and-drop interface – no coding required. However, if needed, agentic workflows created in CrewAI Studio can be exported as Python code for further customization.
Tools and triggers
Enable external systems as tools agents can interact with, or as triggers which start agentic workflows automatically.
Developer APIs
CrewAI's open source framework provides developers with flexible APIs for building agentic workflows depending on the level of abstraction and control needed, with both being clear, concise and intuitive.
AI agents you can trust, and rely on
Tracing
See the details of every LLM and tool call made by AI agents within a workflow, including the inputs, outputs and reasoning behind them – as well as duration, token use and costs.
Training
Train AI agents automatically, or with human feedback, to improve accuracy.
Human in the Loop
Add real-time, human-in-the-loop input to direct AI agents performing critical tasks which require expert human input during live workflow executions.
Built to scale AI agent adoption efficiently
Monitoring
View admin dashboards to gain operational insights on current deployments, performance and usage as well as historical metrics for previous deployments and workflow executions.
Management
Train AI agents automatically, or with human feedback, to improve accuracy.
Serverless Architecture
Add real-time, human-in-the-loop input to direct AI agents performing critical tasks which require expert human input during live workflow executions.
The Agent Management Platform
CrewAI AMP enables enterprises to accelerate the adoption of AI agents across departments, business units and teams by supporting every stage from initial development to production scaling, and to do it efficiently and reliably.
Build
A crew of specialized AI agents can be built in minutes with CrewAI Studio, a visual editor with a drag-and-drop interface and an AI copilot for assistance. However, developers and engineers can take advantage of both object and event-based APIs to apply advanced options.
CrewAI Studio
Empower anyone within an organization to build agentic workflows without requiring technical expertise.
CrewAI API
Build agentic workflows programmatically via APIs that provide greater control and customization.
Integrate
AI agents can interact with business apps such as Asana, Gmail, HubSpot, Microsoft Teams, Salesforce, Slack and Zendesk via native integrations, while custom tools can be created using CrewAI APIs and added to a private tool repository for use by AI agents within the organization.
CrewAI Integrations
Provide AI agents with access to the tools and business apps they need to perform complex tasks.
CrewAI API
Create custom tools that allow AI agents to interact with internal, proprietary applications and systems.
Observe
Complete visibility is required to build trust in AI agents, ensure they are performing tasks as expected and identify any steps where they can benefit from additional instructions. CrewAI's tracing enables AI builders to see what AI agents are doing in real time, and why.
CrewAI Tracing
See precisely how teams of AI agents plan tasks, prompt LLMs, call tools and interpret results.
Optimize
AI agent training, with and without human feedback, helps AI agents learn to produce repeatable, reliable outcomes, while agentic workflows can be tested with multiple LLMs in order to identify the model which produces the optimal balance of cost per token and quality.
AI agent training
Improve AI agents by performing automated, iterative training which discovers and applies relevant suggestions.
LLM testing
Experiment with different LLMs to see which models perform better on specific tasks.
Manage
Performance metrics and usage dashboards allow for continuous monitoring of agentic workflows, and with role-based access control (RBAC), deployment history and streaming logs too, enable admins and operators to manage thousands of agents and workflows efficiently.
Usage Dashboard
Monitor everything from agentic workflows created, deployed and executed to performance and errors.
Workflow Executions
Track current and previous agentic workflow executions based on status, time and type.
Scale
CrewAI AMP, whether on CrewAI or customer-managed infrastructure, scales to millions of agentic workflow executions. However, equally as important, it is designed to help organizations scale the use of agentic AI through the features such as reusable agents and tools.
Agent Repository
Share AI agents for reuse in agentic workflows created by other business units, departments and teams.
Tool Repository
Built custom, reusable tools so AI agents can interact with in-house systems and apps, and avoid duplicating efforts.
Ready to get started?
CrewAI AMP Cloud
Manage the full AI agent lifecycle — build, test, deploy, and scale — with a visual editor and ready-to-use tools.
CrewAI AMP Factory
All the power of AMP Cloud, deployed securely on your own infrastructure — on-prem or private VPCs in AWS, Azure, or GCP.
CrewAI OSS
An open-source orchestration framework with high-level abstractions and low-level APIs for building complex, agent-driven workflows.