Typist and ownscribe are both AI meeting assistants for recording, transcription, and summaries, compared here on pricing, features, and workflow fit. Typist: AI speech-to-text service that converts audio and video into text and exports captions, with tiered models for speed or accuracy. ownscribe: Local-first command-line tool that records, transcribes, and summarizes meetings on macOS entirely on-device, with natural-language search across notes. They overlap on ai-meeting-assistants, so the right pick depends on team size, budget, and which meeting workflows you automate.
For ai-meeting-assistants workflows, shortlist Typist when transcribing recorded interviews and research or client calls matters most, and ownscribe when developers capturing and summarizing meetings from the terminal on a mac matters most. Both record across Zoom, Google Meet, and Microsoft Teams; trial each on real meetings before committing.
AI speech-to-text service that converts audio and video into text and exports captions, with tiered models for speed or accuracy.
Audio and video to text transcription across many file formatsExport to SRT subtitles, WebVTT captions, DOCX, PDF, and TXTMultiple transcription models trading off speed and accuracy
Local-first command-line tool that records, transcribes, and summarizes meetings on macOS entirely on-device, with natural-language search across notes.
Typist vs ownscribe: Pricing, Features & Recommendation | Hosiqo
Local-first recording, transcription, and summarization via CLILocal summarization with a built-in Phi-4-mini model, plus Ollama and OpenAI-compatible backendsMultiple summary templates (meeting, lecture, brief) and silence auto-stop
Typist is a free tier with paid upgrades (freemium); ownscribe is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
Audio and video to text transcription across many file formats
Local-first recording, transcription, and summarization via CLI
Standout feature
Export to SRT subtitles, WebVTT captions, DOCX, PDF, and TXT
System audio capture on macOS 14.2+ through Core Audio
Team usage
Multiple transcription models trading off speed and accuracy
WhisperX transcription with word-level timestamps
Integrations
Speaker identification on the highest-accuracy tier
Optional speaker diarization via PyAnnote
Languages & capture
Word-level and segment-level timestamps for clean subtitle timing
Local summarization with a built-in Phi-4-mini model, plus Ollama and OpenAI-compatible backends
Best-fit workflow
Support for a wide range of languages and accents
Natural-language search across meeting notes with the ask command
Best for
Typist
Choose Typist if you need transcribing recorded interviews and research or client calls — strengths include clean subtitle exports (srt and webvtt) that import into video editors.
ownscribe
Choose ownscribe if you need developers capturing and summarizing meetings from the terminal on a mac — strengths include runs entirely on-device with no data sent to external servers.
Pros & cons
Typist
+ Clean subtitle exports (SRT and WebVTT) that import into video editors
+ Choice of models lets users prioritize speed or accuracy per job
- Speaker identification is limited to the top tier
ownscribe
+ Runs entirely on-device with no data sent to external servers
+ MIT-licensed and scriptable, fitting developer and terminal-driven workflows
- Command-line only, with no graphical interface
FAQ
Is Typist or ownscribe better for AI meeting notes?
It depends on your workflow. Typist is strong for transcribing recorded interviews and research or client calls, while ownscribe is strong for developers capturing and summarizing meetings from the terminal on a mac. Both transcribe and summarize meetings.
How do Typist and ownscribe compare on price?
Typist is a free tier with paid upgrades and ownscribe is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Can I use both Typist and ownscribe?
Yes. Many teams run more than one meeting assistant when the workflows are complementary and the budget is justified.