Agno is a comprehensive runtime for developing, deploying, and managing scalable agentic software, including single agents, coordinated teams, and structured workflows. It provides a framework for building, a stateless FastAPI runtime for serving, and a control plane for production monitoring. Agno operates within the user's infrastructure, ensuring data ownership and auditability.

LangGraph is a low-level orchestration framework and runtime for building and deploying long-running, stateful agents. It provides core capabilities like durable execution, human-in-the-loop interactions, and comprehensive memory management. While it integrates seamlessly with LangChain components, it can be used independently for fine-grained control over agent workflows.

• +Provides a complete runtime for agentic software, supporting agents, teams, and workflows.
• +Offers 100+ integrations for building agents with memory, knowledge, and guardrails.
• +Serves systems as scalable, stateless, session-scoped FastAPI backends for production.
• +Includes AgentOS UI for testing, monitoring, and managing systems in production.
• +Ensures per-user and per-session isolation with native tracing and full auditability.
• +Runs in user's infrastructure, providing full data ownership and control.

• +Provides durable execution, allowing agents to persist through failures and resume from where they left off.
• +Supports human-in-the-loop interactions by enabling inspection and modification of agent state at any point.
• +Offers comprehensive memory capabilities for short-term reasoning and long-term state persistence across sessions.
• +Integrates with LangSmith for deep visibility, debugging, tracing, and evaluation of agent behavior.
• +Designed for production-ready deployment of scalable, stateful, and long-running agent systems.

• −The strong specialization in 'agentic software' may introduce complexity or be over-engineered for simpler, non-agentic applications.
• −Requires users to manage their own infrastructure, which adds operational overhead compared to a fully managed service.
• −Building and governing 'distributed, governed multi-agent systems' can entail a significant learning curve and implementation complexity.

• −LangGraph is very low-level and does not abstract prompts or architecture, requiring more manual configuration.
• −It is not recommended for users just getting started with agents or those seeking a higher-level abstraction.
• −Requires familiarity with components like models and tools before effective use.

State is managed as stateless, session-scoped operations, with sessions, memory, knowledge, and traces persisted in the user's database.

LangGraph manages state through a comprehensive memory system for long-running agents, supporting both short-term working memory and long-term memory across sessions, allowing state inspection and modification.