Plano
An AI-native proxy server built on Envoy that handles routing, observability, and safety policies for multi-agent AI applications.
🔗 Visit Plano
Description
When you build an app that uses several different AI agents working together, you quickly run into plumbing problems: which agent talks to which model, how do you watch what's happening when something goes wrong, how do you keep it all inside your own network for compliance. Plano is infrastructure built specifically to handle that plumbing, so your application code can focus on what the agents actually do.
Plano is an AI-native proxy server and data plane for multi-agent applications, built on Envoy by contributors to that project. It handles agent orchestration and low-latency routing, model routing (by name, alias, or automatic preference), "Agentic Signals" for zero-code observability (OTEL traces and metrics without instrumenting your own code), and Filter Chains for moderation/safety policies. It supports on-premises deployment, which matters for regulated industries, and is framework-agnostic, working as a sidecar regardless of which agent framework you're using. It's open source (Apache-2.0) with adoption reported from companies like HuggingFace, T-Mobile, HP, and SanDisk, positioning it against alternatives like LangChain or LiteLLM for the specific job of production-grade multi-agent infrastructure rather than agent-building itself.
💬 Our review
The short version: Plano is infrastructure plumbing for multi-agent AI applications — routing, observability, and safety policies handled at the proxy layer, built on Envoy, so you don't have to bolt that logic into every agent yourself.
Its differentiators are real: zero-code observability (traces and metrics without instrumenting your agent code) and on-premises deployment support matter a lot once you're running multi-agent systems in a regulated or security-conscious environment — most lighter-weight routing libraries don't offer either.
The tradeoff is that it's infrastructure, not a batteries-included agent framework — you still need your own agents and models; Plano just sits between them. Production deployment also requires either your own LLM or external API keys, and detailed production pricing isn't public (you'd need to reach out via Discord). If you're already running multiple AI agents in production and need routing/observability/compliance at the infrastructure layer, it's a serious option built by people who know Envoy. If you're still prototyping a single agent, it's more infrastructure than you need yet.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Open source (Apache-2.0), gratuit en développement (région US-central hébergée). Déploiement production nécessite LLM local ou clés API externes ; tarifs production non publics (contact Discord).
Pros
Bâti sur Envoy par des contributeurs du projet
Déploiement on-premises pour environnements réglementés
Observabilité zéro-code (traces/metrics OTEL)
Agnostique du framework d'agents utilisé
Cons
Tarification production non publique
Nécessite son propre LLM ou des clés API externes
Courbe d'apprentissage de l'orchestration