Plano
Build agents faster, and deliver them reliably to production
Plano launched on January 6, 2026 with 90 votes, #388 of 14,585 launches that month and more than 95% of that year's launches.
What it does
Plano is delivery infrastructure for agentic apps. An AI-native proxy and dataplane that centralizes functionality that shouldn’t be bespoke in every codebase. For e.g. agent routing & orchestration, guardrail hooks, learning signals/traces, and smart routing APIs across LLMs. Use any AI framework, and ship agents to production faster. With Plano, developers stay focused on core product logic of agents. Product teams learn faster, and engineering teams standardize policies across agents.
Build agents faster and deliver them reliably to production. Plano is an AI-native proxy and data plane for agent orchestration, LLM routing, guardrails, and observability.
Build agents faster, and deliver them reliably to production - by offloading the critical plumbing work to Plano. Plano is an AI-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. Use any language, AI framework, and deliver agents to productions quickly with Plano. Developers can focus more on core product logic of agents. 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. Building agents is hard enough. The…from planoai.dev
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Arch2024 · github.com · ▲314Hey HN — I’m Adil from Katanemo (with Salman, Shuguang, and Meiyu) We previously shared an early version of this project as ArchGW. Based on customer feedback, the scope expanded from “LLM routing and model access” into something broader: delivery infrastructure for agentic applications. We renamed it to Plano and reworked the architecture accordingly. The problem On-the-ground AI practitioners will tell you that calling an LLM is not the hard part. The really hard part is delivering agentic applications to production quickly and reliably, then iterating without rewriting system code every…
SimplAI2025 · simplai.ai · ▲589Hey HN, I've been building SimplAI for the past several months — it's a platform for building, testing, and deploying LLM-powered agents and multi-step workflows. The problem I kept running into: spinning up an AI agent pipeline means stitching together prompt management, tool calling, memory, evals, and deployment — often from scratch every time. SimplAI tries to be the layer that handles all of that so you can focus on what your agent actually does. What it does: - Visual + code-first workflow builder for chaining LLM calls, tools, and APIs - Built-in prompt versioning and A/B testing…
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