--- title: "future-agi vs plano" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-future-agi-vs-katanemo-plano" tools: ["future-agi-future-agi", "katanemo-plano"] --- # future-agi vs plano *GraphCanon updated Sep 20, 2026* ## Verdict Pick future-agi if future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via,; pick plano if plano is an AI-native proxy and data plane for agentic applications built with Rust under the Apache-2.0 license, focusing on smart LLM routing capabilities alongside. [future-agi](https://futureagi.com) reports 2.0k GitHub stars, 627 forks, and 961 open issues, last pushed Sep 18, 2026. [plano](https://planoai.dev) has 7.1k stars, 483 forks, and 140 open issues, last pushed Aug 19, 2026. Figures are from public GitHub metadata via [future-agi's repository](https://github.com/future-agi/future-agi) and [plano's repository](https://github.com/katanemo/plano). | | [future-agi](/tools/future-agi-future-agi.md) | [plano](/tools/katanemo-plano.md) | | --- | --- | --- | | Tagline | Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications | An AI-native proxy and data plane for agentic apps | | Stars | 2,032 | 7,058 | | Forks | 627 | 483 | | Open issues | 961 | 140 | | Language | Python | Rust | | Adopt for | Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via, | Plano is an AI-native proxy and data plane for agentic applications built with Rust under the Apache-2.0 license, focusing on smart LLM routing capabilities alongside orchestration and observability features. | | Persona | - | - | | Runtime | - | - | | License | Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms. | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability, LLM Frameworks | AI Agents, Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [future-agi](/tools/future-agi-future-agi.md) | [plano](/tools/katanemo-plano.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 31d | | Open issues (now) | 961 | 140 | | Stars delta | +473 (30d) | +54 (30d) | | Open issues delta | +365 (30d) | +2 (30d) | | Full report | [trust report](/tools/future-agi-future-agi/trust.md) | [trust report](/tools/katanemo-plano/trust.md) | ## Decision facts: future-agi - **Pricing:** freemium - The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing. - **Requirements:** Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment. - **Adopt for:** Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via, - **License detail:** Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms. ## Decision facts: plano - **Pricing:** freemium - Freely available under Apache-2.0 license but potential for premium services around support and advanced features. - **Requirements:** Min 1 GB RAM - **Adopt for:** Plano is an AI-native proxy and data plane for agentic applications built with Rust under the Apache-2.0 license, focusing on smart LLM routing capabilities alongside orchestration and observability features. ## Choose when ### Choose future-agi if… - future-agi is primarily Python; plano is Rust. - Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.. - Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.. - Tags unique to future-agi: ai-agents, ai-evals, ai-optimization, ai-simulations. - Also covers LLM Frameworks. - You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ### Choose plano if… - plano is primarily Rust; future-agi is Python. - Pricing: Freely available under Apache-2.0 license but potential for premium services around support and advanced features.. - Requirements: Min 1 GB RAM. - Tags unique to plano: agency-apps, llm-proxy, llm-routing, observability. - Also covers Inference & Serving. - You are working on building complex multi-agent workflows where intelligent LLM (Language Model) routing is required. ## When NOT to use future-agi - You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. - You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. - Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source. ## When NOT to use plano - If your application does not require deep orchestration or smart routing between multiple models, choosing Plano might introduce unnecessary complexity. - For scenarios where minimal intervention routing is preferred without advanced observability and guardrail features, this tool may over-deliver on certain functionalities, possibly increasing overhead ## Common questions ### What is the difference between future-agi and plano? future-agi: Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. plano: An AI-native proxy and data plane for agentic apps. See the comparison table for live GitHub stats and shared categories. ### When should I choose future-agi over plano? Choose future-agi over plano when future-agi is primarily Python; plano is Rust; Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.; Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.; Tags unique to future-agi: ai-agents, ai-evals, ai-optimization, ai-simulations; Also covers LLM Frameworks; You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ### When should I choose plano over future-agi? Choose plano over future-agi when plano is primarily Rust; future-agi is Python; Pricing: Freely available under Apache-2.0 license but potential for premium services around support and advanced features.; Requirements: Min 1 GB RAM; Tags unique to plano: agency-apps, llm-proxy, llm-routing, observability; Also covers Inference & Serving; You are working on building complex multi-agent workflows where intelligent LLM (Language Model) routing is required. ### When should I avoid future-agi? You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source. ### When should I avoid plano? If your application does not require deep orchestration or smart routing between multiple models, choosing Plano might introduce unnecessary complexity. For scenarios where minimal intervention routing is preferred without advanced observability and guardrail features, this tool may over-deliver on certain functionalities, possibly increasing overhead ### Is future-agi or plano more popular on GitHub? plano has more GitHub stars (7,058 vs 2,032). Stars measure visibility, not whether either tool fits your constraints. ### Are future-agi and plano open source? Yes - both are open-source projects on GitHub (future-agi: Apache-2.0, plano: Apache-2.0). ### Where can I find alternatives to future-agi or plano? GraphCanon lists graph-backed alternatives at [future-agi alternatives](/tools/future-agi-future-agi/alternatives) and [plano alternatives](/tools/katanemo-plano/alternatives) ([future-agi markdown twin](/tools/future-agi-future-agi/alternatives.md), [plano markdown twin](/tools/katanemo-plano/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/future-agi-future-agi-vs-katanemo-plano.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, future-agi or plano? future-agi: Very active. plano: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for future-agi and plano? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [future-agi trust report](/tools/future-agi-future-agi/trust); [plano trust report](/tools/katanemo-plano/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-future-agi`](/api/graphcanon/graph?tool=future-agi-future-agi) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_