Plano is a models-native proxy and dataplane for agents that handles critical plumbing work in AI - agent routing and orchestration, rich agentic traces, guardrail hooks, and smart model routing APIs for LLMs. It serves as a framework-friendly, protocol-native fabric that lets developers focus on what really matters: their agents' product logic.

Plano provides agent routing and orchestration capabilities, rich agentic traces for observability, guardrail hooks for security, and smart model routing APIs across LLMs. The platform handles routing, observability, and policy hooks as a models-native sidecar, offering centralized policies and access controls across every agent and LLM.

Plano takes over the plumbing work that slows teams down when handling and processing prompts, including detecting and blocking jailbreaks, routing tasks to the right model or agent for better accuracy, applying context engineering hooks, and centralizing observability across agentic interactions. It offers a delightful developer experience with a simple configuration file that describes the types of prompts your agentic app supports.

The platform enables developers to focus more on core product logic of agents, allows product teams to accelerate feedback loops for reinforcement learning, and helps engineering teams standardize policies across agents for safer, more reliable scaling. It supports multi-agent systems without framework lock-in and provides production signals for continuous improvement.

Plano is designed for developers building agentic applications, product teams working with AI agents, and engineering teams needing to standardize AI policies. It supports use cases including agent orchestration, context engineering, reinforcement learning, centralized security, and on-premises deployment for regulated environments.