--- title: "future-agi vs humanbound" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-future-agi-vs-humanbound-humanbound" tools: ["future-agi-future-agi", "humanbound-humanbound"] --- # future-agi vs humanbound *GraphCanon updated Aug 9, 2026* ## Verdict Pick future-agi if future-AGI is an open-source toolkit for evaluating and improving LLMs and AI agents. It includes features like tracing, evaluations, simulations, datasets, gateway operations, and guardrails; pick humanbound if humanbound is an adversarial testing engine and SDK in Python designed specifically for evaluating the robustness of AI agents against various security threats. [future-agi](https://futureagi.com) reports 1.6k GitHub stars, 449 forks, and 596 open issues, last pushed Aug 1, 2026. [humanbound](https://docs.humanbound.ai/) has 118 stars, 13 forks, and 10 open issues, last pushed Aug 6, 2026. Figures are from public GitHub metadata via [future-agi's repository](https://github.com/future-agi/future-agi) and [humanbound's repository](https://github.com/humanbound/humanbound). | | [future-agi](/tools/future-agi-future-agi.md) | [humanbound](/tools/humanbound-humanbound.md) | | --- | --- | --- | | Tagline | End-to-end platform for evaluating, observing, and improving LLM and AI agent applications | Adversarial Testing Engine and SDK for AI Agents | | Stars | 1,559 | 118 | | Forks | 449 | 13 | | Open issues | 596 | 10 | | Language | Python | Python | | Adopt for | Future-AGI is an open-source toolkit for evaluating and improving LLMs and AI agents. It includes features like tracing, evaluations, simulations, datasets, gateway operations, and guardrails. | humanbound is an adversarial testing engine and SDK in Python designed specifically for evaluating the robustness of AI agents against various security threats. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [future-agi](/tools/future-agi-future-agi.md) | [humanbound](/tools/humanbound-humanbound.md) | | --- | --- | --- | | Days since push | 1d | 3d | | Open issues (now) | 596 | 10 | | Full report | [trust report](/tools/future-agi-future-agi/trust.md) | [trust report](/tools/humanbound-humanbound/trust.md) | ## Decision facts: future-agi - **Pricing:** freemium - Future-AGI is open-source under the Apache 2.0 license, allowing for free use but with potential paid services through deployment and support channels. - **Requirements:** Min 4 GB RAM; Requires Docker - **Adopt for:** Future-AGI is an open-source toolkit for evaluating and improving LLMs and AI agents. It includes features like tracing, evaluations, simulations, datasets, gateway operations, and guardrails. ## Decision facts: humanbound - **Adopt for:** humanbound is an adversarial testing engine and SDK in Python designed specifically for evaluating the robustness of AI agents against various security threats. ## Choose when ### Choose future-agi if… - License: future-agi is Apache-2.0, humanbound is Other. - Pricing: Future-AGI is open-source under the Apache 2.0 license, allowing for free use but with potential paid services through deployment and support channels.. - Requirements: Min 4 GB RAM; Requires Docker. - Tags unique to future-agi: ai-gateway, docker-compose, evals, llm. - future-agi ships Docker support for self-hosted deployment. - - Use Future-AGI when you require an end-to-end evaluation platform that supports self-hosting through Docker Compose or VM-based services on public clouds. ### Choose humanbound if… - License: humanbound is Other, future-agi is Apache-2.0. - Tags unique to humanbound: adversarial-testing, agentic-ai, ai-agents, llm security. - When you need to test your AI agent's resilience against prompt injection attacks, utilize humanbound’s specialized features tailored for this purpose ## When NOT to use future-agi - - Avoid using Future-AGI if you require Kubernetes or Helm support as of the current state; though these are planned for future release, they are not yet available. - - If your deployment strategy relies on a managed service like AWS Marketplace, consider other options since it is currently 'Coming Soon'. ## When NOT to use humanbound - Avoid using humanbound if your project does not involve AI agents or is not concerned about adversarial robustness since the tool's functionality might be overly specific - Do not use humanbound in environments where an open-source solution is restricted, particularly considering its licensing and trademark policies ## Common questions ### What is the difference between future-agi and humanbound? future-agi: End-to-end platform for evaluating, observing, and improving LLM and AI agent applications. humanbound: Adversarial Testing Engine and SDK for AI Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose future-agi over humanbound? Choose future-agi over humanbound when License: future-agi is Apache-2.0, humanbound is Other; Pricing: Future-AGI is open-source under the Apache 2.0 license, allowing for free use but with potential paid services through deployment and support channels.; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to future-agi: ai-gateway, docker-compose, evals, llm; future-agi ships Docker support for self-hosted deployment; - Use Future-AGI when you require an end-to-end evaluation platform that supports self-hosting through Docker Compose or VM-based services on public clouds. ### When should I choose humanbound over future-agi? Choose humanbound over future-agi when License: humanbound is Other, future-agi is Apache-2.0; Tags unique to humanbound: adversarial-testing, agentic-ai, ai-agents, llm security; When you need to test your AI agent's resilience against prompt injection attacks, utilize humanbound’s specialized features tailored for this purpose. ### When should I avoid future-agi? - Avoid using Future-AGI if you require Kubernetes or Helm support as of the current state; though these are planned for future release, they are not yet available. - If your deployment strategy relies on a managed service like AWS Marketplace, consider other options since it is currently 'Coming Soon'. ### When should I avoid humanbound? Avoid using humanbound if your project does not involve AI agents or is not concerned about adversarial robustness since the tool's functionality might be overly specific Do not use humanbound in environments where an open-source solution is restricted, particularly considering its licensing and trademark policies ### Is future-agi or humanbound more popular on GitHub? future-agi has more GitHub stars (1,559 vs 118). Stars measure visibility, not whether either tool fits your constraints. ### Are future-agi and humanbound open source? Yes - both are open-source projects on GitHub (future-agi: Apache-2.0, humanbound: Other). ### Where can I find alternatives to future-agi or humanbound? GraphCanon lists graph-backed alternatives at [future-agi alternatives](/tools/future-agi-future-agi/alternatives) and [humanbound alternatives](/tools/humanbound-humanbound/alternatives) ([future-agi markdown twin](/tools/future-agi-future-agi/alternatives.md), [humanbound markdown twin](/tools/humanbound-humanbound/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-humanbound-humanbound.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, future-agi or humanbound? future-agi: Very active. humanbound: Very active. 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 humanbound? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [future-agi trust report](/tools/future-agi-future-agi/trust); [humanbound trust report](/tools/humanbound-humanbound/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/_