--- title: "future-agi vs RagaAI-Catalyst" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-future-agi-vs-raga-ai-hub-ragaai-catalyst" tools: ["future-agi-future-agi", "raga-ai-hub-ragaai-catalyst"] --- # future-agi vs RagaAI-Catalyst *GraphCanon updated Aug 20, 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 RagaAI-Catalyst if ragaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL. [future-agi](https://futureagi.com) reports 1.6k GitHub stars, 449 forks, and 596 open issues, last pushed Aug 1, 2026. [RagaAI-Catalyst](https://catalyst.raga.ai/) has 16k stars, 3.6k forks, and 34 open issues, last pushed Feb 11, 2026. Figures are from public GitHub metadata via [future-agi's repository](https://github.com/future-agi/future-agi) and [RagaAI-Catalyst's repository](https://github.com/raga-ai-hub/RagaAI-Catalyst). | | [future-agi](/tools/future-agi-future-agi.md) | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | | --- | --- | --- | | Tagline | End-to-end platform for evaluating, observing, and improving LLM and AI agent applications | Python SDK for AI agent observability and evaluation | | Stars | 1,559 | 16,148 | | Forks | 449 | 3,565 | | Open issues | 596 | 34 | | 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. | RagaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | 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) | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 1d | 189d | | Open issues (now) | 596 | 34 | | Stars delta | Unknown | +5 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/future-agi-future-agi/trust.md) | [trust report](/tools/raga-ai-hub-ragaai-catalyst/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: RagaAI-Catalyst - **Adopt for:** RagaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL ## Choose when ### Choose future-agi if… - 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 RagaAI-Catalyst if… - Tags unique to RagaAI-Catalyst: agentic-ai, agentic-ai-development, agentneo, agents. - When you need comprehensive tools for the observability of complex multi-agentic systems. - More GitHub stars (16k vs 1.6k) - visibility, not fit. ## 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 RagaAI-Catalyst - When you prefer a language-agnostic solution or require support outside of the Python ecosystem. - If your primary need is focused solely on basic monitoring without advanced debugging and evaluation features. - For projects that do not utilize multi-agentic systems or do not benefit from timeline and execution graph visualizations. - In scenarios where a fully managed service with no self-hosting requirements is preferred. ## Common questions ### What is the difference between future-agi and RagaAI-Catalyst? future-agi: End-to-end platform for evaluating, observing, and improving LLM and AI agent applications. RagaAI-Catalyst: Python SDK for AI agent observability and evaluation. See the comparison table for live GitHub stats and shared categories. ### When should I choose future-agi over RagaAI-Catalyst? Choose future-agi over RagaAI-Catalyst when 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 RagaAI-Catalyst over future-agi? Choose RagaAI-Catalyst over future-agi when Tags unique to RagaAI-Catalyst: agentic-ai, agentic-ai-development, agentneo, agents; When you need comprehensive tools for the observability of complex multi-agentic systems; More GitHub stars (16k vs 1.6k) - visibility, not fit. ### 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 RagaAI-Catalyst? When you prefer a language-agnostic solution or require support outside of the Python ecosystem. If your primary need is focused solely on basic monitoring without advanced debugging and evaluation features. For projects that do not utilize multi-agentic systems or do not benefit from timeline and execution graph visualizations. In scenarios where a fully managed service with no self-hosting requirements is preferred. ### Is future-agi or RagaAI-Catalyst more popular on GitHub? RagaAI-Catalyst has more GitHub stars (16,148 vs 1,559). Stars measure visibility, not whether either tool fits your constraints. ### Are future-agi and RagaAI-Catalyst open source? Yes - both are open-source projects on GitHub (future-agi: Apache-2.0, RagaAI-Catalyst: Apache-2.0). ### Where can I find alternatives to future-agi or RagaAI-Catalyst? GraphCanon lists graph-backed alternatives at [future-agi alternatives](/tools/future-agi-future-agi/alternatives) and [RagaAI-Catalyst alternatives](/tools/raga-ai-hub-ragaai-catalyst/alternatives) ([future-agi markdown twin](/tools/future-agi-future-agi/alternatives.md), [RagaAI-Catalyst markdown twin](/tools/raga-ai-hub-ragaai-catalyst/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-raga-ai-hub-ragaai-catalyst.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, future-agi or RagaAI-Catalyst? future-agi: Very active. RagaAI-Catalyst: Slowing. 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 RagaAI-Catalyst? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [future-agi trust report](/tools/future-agi-future-agi/trust); [RagaAI-Catalyst trust report](/tools/raga-ai-hub-ragaai-catalyst/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/_