Comparison Preset
Choose CrewAI due to its superior security posture, which is a critical factor for enterprise adoption. Agno reports a CRITICAL vulnerability, posing a significant risk that outweighs its other enterprise-friendly features like the Apache-2.0 license and a stateless runtime. CrewAI has zero known vulnerabilities and includes essential enterprise capabilities such as RBAC and team management. Both frameworks have an excellent bus factor score of 8/10, but the security issue makes Agno a difficult choice for risk-averse environments. This decision prioritizes security and risk mitigation.
Overview
The bottom line ā what this framework is, who it's for, and when to walk away.
Bottom Line Up Front
Agno provides an SDK, a stateless FastAPI runtime (AgentOS), and a control plane for building and deploying production-ready AI agent platforms. It supports agents with memory, knowledge, and integrations, offering cloud-agnostic deployment.
CrewAI is a framework for designing and orchestrating multi-agent AI systems, providing built-in guardrails, memory, and observability. It supports structured agent outputs, long-running workflow persistence, and various process types including human-in-the-loop. Enterprise features facilitate deployment, integration with external services, and team management.
Best For
Deploying, monitoring, and managing production-grade AI agent platforms with structured workflows.
Orchestrating robust, multi-agent AI systems with built-in guardrails, memory, and observability.
Avoid If
no data
no data
Strengths
- +Provides a rich SDK for building agents, teams, and complex workflows.
- +Offers extensive integrations (100+) for agent capabilities.
- +Features a production-ready runtime (AgentOS) based on a stateless FastAPI backend.
- +Includes an integrated control plane with a UI for monitoring and management.
- +Supports deployment across multiple cloud providers and containerization options, including AWS, GCP, Azure, Kubernetes, and Docker.
- +Built-in guardrails, memory, knowledge, and observability for multi-agent systems.
- +Supports structured agent outputs using Pydantic.
- +Enables orchestration of long-running, stateful workflows with persistence and resumption.
- +Allows defining diverse process types: sequential, hierarchical, hybrid, with human-in-the-loop triggers.
- +Provides enterprise features for deployment, environment management, and live run monitoring.
- +Offers extensive integrations with external services like Gmail, Slack, Salesforce, and Bedrock Agents.
- +Includes team management capabilities with Role-Based Access Control (RBAC) for production automations.
Weaknesses
Project Health
Is this project alive, well-maintained, and safe to bet on long-term?
Bus Factor Score
Maintainers
Open Issues
Fit
Does it support the workflows, patterns, and capabilities your team actually needs?
State Management
The SDK enables agents to manage internal state via its 'memory' feature, while the AgentOS runtime itself operates statelessly.
The framework manages state within flows, allowing for persistence and resuming long-running workflows.
Cost & Licensing
What does it actually cost? License type, pricing model, and hidden fees.
License
Perspective
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