Speakr and TwinMind are both AI meeting assistants for recording, transcription, and summaries, compared here on pricing, features, and workflow fit. Speakr: Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search. TwinMind: Browser-extension and mobile AI meeting assistant that transcribes calls in real time on-device and turns them into searchable 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 Speakr when privacy-conscious teams self-hosting transcription and summaries for internal meetings matters most, and TwinMind when professionals who want hands-free notes during back-to-back video calls matters most. Both record across Zoom, Google Meet, and Microsoft Teams; trial each on real meetings before committing.
Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search.
Configurable AI models compatible with OpenAI, OpenRouter, and local modelsCustomizable summaries plus an action-items view for decisions and tasksMulti-user support with SSO, group workspaces, and admin dashboard
Browser-extension and mobile AI meeting assistant that transcribes calls in real time on-device and turns them into searchable notes.
AI chat to query and search past conversationsAutomatic AI summaries and action items after each meetingChrome browser extension for Google Meet, Zoom, and Microsoft Teams
Speakr is a free tier with paid upgrades (freemium); TwinMind is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
Self-hosted transcription with automatic language detection
Chrome browser extension for Google Meet, Zoom, and Microsoft Teams
Standout feature
Optional AI-powered speaker diarization
Real-time transcription with on-device audio capture (no separate meeting bot)
Team usage
Customizable summaries plus an action-items view for decisions and tasks
Automatic AI summaries and action items after each meeting
Integrations
Per-recording chat and an Inquire Mode for semantic search across the whole library
AI chat to query and search past conversations
Languages & capture
System and browser-tab audio capture
Companion mobile app for in-person and on-the-go capture
Best-fit workflow
Multi-user support with SSO, group workspaces, and admin dashboard
Multilingual transcription across many languages
Best for
Speakr
Choose Speakr if you need privacy-conscious teams self-hosting transcription and summaries for internal meetings — strengths include runs entirely on the user's own infrastructure for full data control.
TwinMind
Choose TwinMind if you need professionals who want hands-free notes during back-to-back video calls — strengths include bot-free capture avoids a visible recorder joining the call.
Pros & cons
Speakr
+ Runs entirely on the user's own infrastructure for full data control
+ Action-item extraction and per-recording chat go beyond plain transcripts
- Current releases are alpha-stage and may not be production-stable
TwinMind
+ Bot-free capture avoids a visible recorder joining the call
+ Works across desktop browser and mobile in one product
- Browser-extension capture depends on running meetings in a supported browser
FAQ
Is Speakr or TwinMind better for AI meeting notes?
It depends on your workflow. Speakr is strong for privacy-conscious teams self-hosting transcription and summaries for internal meetings, while TwinMind is strong for professionals who want hands-free notes during back-to-back video calls. Both transcribe and summarize meetings.
How do Speakr and TwinMind compare on price?
Speakr is a free tier with paid upgrades and TwinMind 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 Speakr and TwinMind?
Yes. Many teams run more than one meeting assistant when the workflows are complementary and the budget is justified.