Agno provides an SDK and runtime (AgentOS) for building, running, and managing agent platforms. It enables the creation of multi-agent systems and step-based workflows, offering production features like isolated sessions, RBAC, and data ownership. Teams can deploy intelligent software in their own cloud environments.

Pydantic AI is a Python agent framework for building robust Generative AI applications, leveraging Pydantic validation for type-safety and structured outputs. It offers deep observability integration and supports a wide array of models and providers. The framework emphasizes extensibility and durable execution for reliable agent operations.

• +Provides an SDK for building agents, multi-agent teams, and step-based agentic workflows.
• +AgentOS runtime offers multi-user, isolated sessions with tracing, scheduling, RBAC, and audit logs.
• +Allows running agents as a service with a unified control plane for management.
• +Runs in your cloud using your database, ensuring ownership of session, memory, and trace data.
• +Natively typesafe and multi-modal, suitable for data labeling, extraction, and classification.
• +Can productionize agents built with any framework, model, or cloud.

• +Built by the Pydantic team, leveraging deep expertise in data validation and parsing.
• +Model-agnostic, supporting a wide range of LLMs and providers, with custom model implementation options.
• +Seamlessly integrates with Pydantic Logfire for real-time debugging, tracing, cost tracking, and performance monitoring.
• +Fully type-safe design, reducing runtime errors by catching issues at write-time with static type checking.
• +Provides powerful evaluation capabilities to systematically test agent performance and accuracy over time.
• +Extensible by design, allowing agents to be built from composable capabilities and defined via YAML/JSON.
• +Integrates Model Context Protocol (MCP) and UI event stream standards for external tools and interactive applications.
• +Supports human-in-the-loop tool approval, allowing specific tool calls to require user confirmation.
• +Offers durable execution, enabling agents to preserve progress across failures, errors, or restarts.
• +Provides streamed structured output with immediate validation, ensuring real-time data access.
• +Includes graph support for defining complex application flows using type hints, avoiding spaghetti code.
• +Features a type-safe dependency injection system for tools and instructions, enhancing testability and customization.

AgentOS runtime manages state through multi-user, isolated sessions, allowing users to own their session, memory, and trace data.

The framework enables durable agents to preserve their execution progress across failures and restarts, supporting long-running and asynchronous workflows.