Delivery infrastructure for agentic apps
Build agents faster, and deliver them reliably to prod by offloading plumbing work in AI
WHY PLANO?
Deliver prototypes to production—fast.
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.
Developers can focus more on modeling workflows. Product teams can accelerate feedback loops for reinforcement learning. Engineering teams can standardize policies and access controls across every agent and LLM for safer, more reliable scaling.
Idea to agent — without overhead
LAUNCH FASTER
Focus on core objectives
Building AI agents is hard enough (iterate on prompts and evaluate LLMs, etc), the plumbing work shouldn't add to that complexity. Plano takes care of the critical plumbing work like routing and orchestration to agents that slows you down and locks you into rigid frameworks, freeing developers to innovate on what truly matters.
What's possible with Plano
AGENT ORCHESTRATION
Multi-agent systems without framework lock-in
CONTEXT ENGINEERING
Reusable filters for smarter agents
REINFORCEMENT LEARNING
Production signals for continuous improvement
CENTRALIZED SECURITY
Built-in guardrails and centralized policies
ON-PREMISES DEPLOYMENT
Full data control in regulated environments
Under the hood
Plano is an intelligent (edge and LLM) proxy server designed for agents - to help you focus on core business objectives. Arch handles critical but the pesky tasks related to the handling and processing of prompts, which includes detecting and rejecting jailbreak attempts, intelligent task routing for improved accuracy, mapping user requests into 'backend' functions, and managing the observability of prompts and LLM in a centralized way.
One configuration file to orchestrate
Plano offers a delightful developer experience with a simple configuration file that describes the types of prompts your agentic app supports, a set of APIs that need to be plugged in for agentic scenarios (including retrieval queries) and your choice of LLMs.
