--- title: "amical vs dograh" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/amicalhq-amical-vs-dograh-hq-dograh" tools: ["amicalhq-amical", "dograh-hq-dograh"] --- # amical vs dograh *GraphCanon updated Jul 30, 2026* ## Verdict Pick amical if amical is an open-source AI dictation tool that offers fast offline speech-to-text transcription; pick dograh if self-hosted voice AI platform with speech-to-speech, LLM integration, telephony support. [amical](https://amical.ai) reports 1.5k GitHub stars, 134 forks, and 53 open issues, last pushed Jul 28, 2026. [dograh](https://app.dograh.com) has 5.1k stars, 1.2k forks, and 20 open issues, last pushed Jul 29, 2026. Figures are from public GitHub metadata via [amical's repository](https://github.com/amicalhq/amical) and [dograh's repository](https://github.com/dograh-hq/dograh). | | [amical](/tools/amicalhq-amical.md) | [dograh](/tools/dograh-hq-dograh.md) | | --- | --- | --- | | Tagline | AI Dictation App - Open Source and Local-first | Self-hosted open source voice AI platform | | Stars | 1,469 | 5,064 | | Forks | 134 | 1,185 | | Open issues | 53 | 20 | | Language | TypeScript | Python | | Adopt for | Amical is an open-source AI dictation tool that offers fast offline speech-to-text transcription. | Self-hosted voice AI platform with speech-to-speech, LLM integration, telephony support | | Persona | - | - | | Runtime | - | - | | License | MIT | BSD-2-Clause | | Categories | Speech & Audio | Inference & Serving, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [amical](/tools/amicalhq-amical.md) | [dograh](/tools/dograh-hq-dograh.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 53 | 20 | | Full report | [trust report](/tools/amicalhq-amical/trust.md) | [trust report](/tools/dograh-hq-dograh/trust.md) | ## Decision facts: amical - **Adopt for:** Amical is an open-source AI dictation tool that offers fast offline speech-to-text transcription. ## Decision facts: dograh - **Adopt for:** Self-hosted voice AI platform with speech-to-speech, LLM integration, telephony support ## Choose when ### Choose amical if… - amical is primarily TypeScript; dograh is Python. - License: amical is MIT, dograh is BSD-2-Clause. - Tags unique to amical: ai-note-taking-app, asr, dictate, dictation-tool. - Need for self-hosting solutions ### Choose dograh if… - dograh is primarily Python; amical is TypeScript. - License: dograh is BSD-2-Clause, amical is MIT. - Tags unique to dograh: conversational-ai, local-llm, self-hosted, speech-to-text. - Also covers Inference & Serving. - You need on-premise deployment for better security or data control ## When NOT to use amical - Seeking a cloud-based solution - Requiring seamless integration with web applications - Looking for extensive customization through API access ## When NOT to use dograh - Seeking cloud-managed services without self-hosting capabilities - Need real-time collaboration with non-local models in the cloud - Preference is for tools under different licenses than BSD-2-Clause - Must integrate with platforms that lack native telephony support ## Common questions ### What is the difference between amical and dograh? amical: AI Dictation App - Open Source and Local-first. dograh: Self-hosted open source voice AI platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose amical over dograh? Choose amical over dograh when amical is primarily TypeScript; dograh is Python; License: amical is MIT, dograh is BSD-2-Clause; Tags unique to amical: ai-note-taking-app, asr, dictate, dictation-tool; Need for self-hosting solutions. ### When should I choose dograh over amical? Choose dograh over amical when dograh is primarily Python; amical is TypeScript; License: dograh is BSD-2-Clause, amical is MIT; Tags unique to dograh: conversational-ai, local-llm, self-hosted, speech-to-text; Also covers Inference & Serving; You need on-premise deployment for better security or data control. ### When should I avoid amical? Seeking a cloud-based solution Requiring seamless integration with web applications Looking for extensive customization through API access ### When should I avoid dograh? Seeking cloud-managed services without self-hosting capabilities Need real-time collaboration with non-local models in the cloud Preference is for tools under different licenses than BSD-2-Clause Must integrate with platforms that lack native telephony support ### Is amical or dograh more popular on GitHub? dograh has more GitHub stars (5,064 vs 1,469). Stars measure visibility, not whether either tool fits your constraints. ### Are amical and dograh open source? Yes - both are open-source projects on GitHub (amical: MIT, dograh: BSD-2-Clause). ### Where can I find alternatives to amical or dograh? GraphCanon lists graph-backed alternatives at [amical alternatives](/tools/amicalhq-amical/alternatives) and [dograh alternatives](/tools/dograh-hq-dograh/alternatives) ([amical markdown twin](/tools/amicalhq-amical/alternatives.md), [dograh markdown twin](/tools/dograh-hq-dograh/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/amicalhq-amical-vs-dograh-hq-dograh.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, amical or dograh? amical: Very active. dograh: 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 amical and dograh? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [amical trust report](/tools/amicalhq-amical/trust); [dograh trust report](/tools/dograh-hq-dograh/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=amicalhq-amical`](/api/graphcanon/graph?tool=amicalhq-amical) - 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/_