--- title: "Kiln vs RagaAI-Catalyst" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kiln-ai-kiln-vs-raga-ai-hub-ragaai-catalyst" tools: ["kiln-ai-kiln", "raga-ai-hub-ragaai-catalyst"] --- # Kiln vs RagaAI-Catalyst *GraphCanon updated Aug 23, 2026* ## Verdict Pick Kiln if kiln is a versatile AI systems development toolkit that excels in comprehensive evaluation frameworks for agents, RAG components, and fine-tuning processes; 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. [Kiln](https://kiln.tech) reports 5.0k GitHub stars, 375 forks, and 69 open issues, last pushed Aug 23, 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 [Kiln's repository](https://github.com/Kiln-AI/Kiln) and [RagaAI-Catalyst's repository](https://github.com/raga-ai-hub/RagaAI-Catalyst). | | [Kiln](/tools/kiln-ai-kiln.md) | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | | --- | --- | --- | | Tagline | Build, Evaluate, and Optimize AI Systems | Python SDK for AI agent observability and evaluation | | Stars | 5,034 | 16,148 | | Forks | 375 | 3,565 | | Open issues | 69 | 34 | | Language | Python | Python | | Adopt for | Kiln is a versatile AI systems development toolkit that excels in comprehensive evaluation frameworks for agents, RAG components, and fine-tuning processes. | 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 | Other | Apache-2.0 | | Categories | AI Agents, Data & Retrieval, Evaluation & Observability, Model Training | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Kiln](/tools/kiln-ai-kiln.md) | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 189d | | Open issues (now) | 69 | 34 | | Stars delta | +63 (30d) | +5 (30d) | | Open issues delta | +3 (30d) | 0 (30d) | | Full report | [trust report](/tools/kiln-ai-kiln/trust.md) | [trust report](/tools/raga-ai-hub-ragaai-catalyst/trust.md) | ## Shared compatibility - **Python**: [Kiln](/tools/kiln-ai-kiln.md) - Python runtime; [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) - Python runtime ## Decision facts: Kiln - **Adopt for:** Kiln is a versatile AI systems development toolkit that excels in comprehensive evaluation frameworks for agents, RAG components, and fine-tuning processes. ## 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 Kiln if… - License: Kiln is Other, RagaAI-Catalyst is Apache-2.0. - Tags unique to Kiln: ai, chain-of-thought, collaboration, dataset-generation. - Also covers Data & Retrieval, Model Training. - When you need extensive tools for evaluating custom AI agents ### Choose RagaAI-Catalyst if… - License: RagaAI-Catalyst is Apache-2.0, Kiln is Other. - 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. ## When NOT to use Kiln - If your project strictly requires a lightweight tool without comprehensive dataset management options - Avoid if you do not require advanced synthetic data generation capabilities ## 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 Kiln and RagaAI-Catalyst? Kiln: Build, Evaluate, and Optimize AI Systems. 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 Kiln over RagaAI-Catalyst? Choose Kiln over RagaAI-Catalyst when License: Kiln is Other, RagaAI-Catalyst is Apache-2.0; Tags unique to Kiln: ai, chain-of-thought, collaboration, dataset-generation; Also covers Data & Retrieval, Model Training; When you need extensive tools for evaluating custom AI agents. ### When should I choose RagaAI-Catalyst over Kiln? Choose RagaAI-Catalyst over Kiln when License: RagaAI-Catalyst is Apache-2.0, Kiln is Other; 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. ### When should I avoid Kiln? If your project strictly requires a lightweight tool without comprehensive dataset management options Avoid if you do not require advanced synthetic data generation capabilities ### 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 Kiln or RagaAI-Catalyst more popular on GitHub? RagaAI-Catalyst has more GitHub stars (16,148 vs 5,034). Stars measure visibility, not whether either tool fits your constraints. ### Are Kiln and RagaAI-Catalyst open source? Yes - both are open-source projects on GitHub (Kiln: Other, RagaAI-Catalyst: Apache-2.0). ### Where can I find alternatives to Kiln or RagaAI-Catalyst? GraphCanon lists graph-backed alternatives at [Kiln alternatives](/tools/kiln-ai-kiln/alternatives) and [RagaAI-Catalyst alternatives](/tools/raga-ai-hub-ragaai-catalyst/alternatives) ([Kiln markdown twin](/tools/kiln-ai-kiln/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/kiln-ai-kiln-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, Kiln or RagaAI-Catalyst? Kiln: 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 Kiln and RagaAI-Catalyst? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Kiln trust report](/tools/kiln-ai-kiln/trust); [RagaAI-Catalyst trust report](/tools/raga-ai-hub-ragaai-catalyst/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kiln-ai-kiln`](/api/graphcanon/graph?tool=kiln-ai-kiln) - 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/_