--- title: "ai-gateway vs sagify" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-kenza-ai-sagify" tools: ["ferro-labs-ai-gateway", "kenza-ai-sagify"] --- # ai-gateway vs sagify *GraphCanon updated Aug 25, 2026* ## Verdict Pick ai-gateway if ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment; pick sagify if an accessible tool for managing large language models and other machine learning tasks in Python. [ai-gateway](https://docs.ferrolabs.ai) reports 219 GitHub stars, 33 forks, and 63 open issues, last pushed Aug 7, 2026. [sagify](https://kenza-ai.github.io/sagify/) has 442 stars, 68 forks, and 18 open issues, last pushed Feb 11, 2026. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [sagify's repository](https://github.com/Kenza-AI/sagify). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [sagify](/tools/kenza-ai-sagify.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | LLMs and Machine Learning done easily | | Stars | 219 | 442 | | Forks | 33 | 68 | | Open issues | 63 | 18 | | Language | Go | Python | | Adopt for | ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment. | An accessible tool for managing large language models and other machine learning tasks in Python. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | Offered under the MIT license, allowing broad use for both commercial and non-commercial purposes with few restrictions. | | Categories | Inference & Serving, Model Training | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [sagify](/tools/kenza-ai-sagify.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 2d | 195d | | Open issues (now) | 63 | 18 | | Stars delta | Unknown | 0 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/kenza-ai-sagify/trust.md) | ## Decision facts: ai-gateway - **Adopt for:** ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment. - **License detail:** Apache-2.0 - a permissive free software license ## Decision facts: sagify - **Requirements:** Requires Docker; - Requires Docker to manage environments consistently across different platforms. - **Adopt for:** An accessible tool for managing large language models and other machine learning tasks in Python. - **License detail:** Offered under the MIT license, allowing broad use for both commercial and non-commercial purposes with few restrictions. ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; sagify is Python. - License: ai-gateway is Apache-2.0, sagify is MIT. - Tags unique to ai-gateway: litellm, llm-cost, llm-proxy, openai-compatible. - When you need to integrate more than 30 different LLM services including OpenAI and Anthropic ### Choose sagify if… - sagify is primarily Python; ai-gateway is Go. - License: sagify is MIT, ai-gateway is Apache-2.0. - Requirements: Requires Docker; - Requires Docker to manage environments consistently across different platforms.. - Tags unique to sagify: anthropic, cohere, generative-ai, langchain. - Also covers LLM Frameworks. - - When you need an integrated solution for various aspects of working with LLMs and ML tasks that is easy to understand and use, without deep technical expertise. ## When NOT to use ai-gateway - If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features - For small-scale projects that do not require comprehensive cost analysis tools - When custom integration for specific guardrails is required, as ai-gateway offers generalized settings ## When NOT to use sagify - - When your focus is exclusively on advanced fine-tuning or customization of machine learning models which require deep configuration options tailored to specific needs. - - If you prioritize working within a highly specialized ML ecosystem that has its own set of tools and workflows, as Sagify might not integrate seamlessly with every specialized tool. ## Common questions ### What is the difference between ai-gateway and sagify? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. sagify: LLMs and Machine Learning done easily. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over sagify? Choose ai-gateway over sagify when ai-gateway is primarily Go; sagify is Python; License: ai-gateway is Apache-2.0, sagify is MIT; Tags unique to ai-gateway: litellm, llm-cost, llm-proxy, openai-compatible; When you need to integrate more than 30 different LLM services including OpenAI and Anthropic. ### When should I choose sagify over ai-gateway? Choose sagify over ai-gateway when sagify is primarily Python; ai-gateway is Go; License: sagify is MIT, ai-gateway is Apache-2.0; Requirements: Requires Docker; - Requires Docker to manage environments consistently across different platforms.; Tags unique to sagify: anthropic, cohere, generative-ai, langchain; Also covers LLM Frameworks; - When you need an integrated solution for various aspects of working with LLMs and ML tasks that is easy to understand and use, without deep technical expertise. ### When should I avoid ai-gateway? If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features For small-scale projects that do not require comprehensive cost analysis tools When custom integration for specific guardrails is required, as ai-gateway offers generalized settings ### When should I avoid sagify? - When your focus is exclusively on advanced fine-tuning or customization of machine learning models which require deep configuration options tailored to specific needs. - If you prioritize working within a highly specialized ML ecosystem that has its own set of tools and workflows, as Sagify might not integrate seamlessly with every specialized tool. ### Is ai-gateway or sagify more popular on GitHub? sagify has more GitHub stars (442 vs 219). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and sagify open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, sagify: MIT). ### Where can I find alternatives to ai-gateway or sagify? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [sagify alternatives](/tools/kenza-ai-sagify/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [sagify markdown twin](/tools/kenza-ai-sagify/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/ferro-labs-ai-gateway-vs-kenza-ai-sagify.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or sagify? ai-gateway: Very active. sagify: 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 ai-gateway and sagify? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [sagify trust report](/tools/kenza-ai-sagify/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ferro-labs-ai-gateway`](/api/graphcanon/graph?tool=ferro-labs-ai-gateway) - 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/_