Scriberr and Vexa are both AI meeting assistants for recording, transcription, and summaries, compared here on pricing, features, and workflow fit. Scriberr: Open-source, self-hosted AI audio transcription app that runs Whisper models locally with speaker diarization, summaries, and chat-with-transcript. Vexa: API-first, open-source meeting transcription platform that deploys bots to capture real-time, speaker-labeled transcripts for developers. They overlap on ai-meeting-assistants, ai-transcription, so the right pick depends on team size, budget, and which meeting workflows you automate.
For ai-meeting-assistants, ai-transcription workflows, shortlist Scriberr when privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure matters most, and Vexa when building custom meeting-intelligence features into a product matters most. Both record across Zoom, Google Meet, and Microsoft Teams; trial each on real meetings before committing.
Open-source, self-hosted AI audio transcription app that runs Whisper models locally with speaker diarization, summaries, and chat-with-transcript.
AI summaries with custom prompts via Ollama or OpenAI-compatible providersAutomatic speaker diarization (who said what)Built-in audio recorder and note-taking on transcripts
API-first, open-source meeting transcription platform that deploys bots to capture real-time, speaker-labeled transcripts for developers.
API-first design with REST and WebSocket interfacesData storage with query and export capabilitiesDeployable bots that join meetings via URL to capture audio
Scriberr is a free tier with paid upgrades (freemium); Vexa is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
Local, offline transcription using Whisper models via the WhisperX engine
API-first design with REST and WebSocket interfaces
Standout feature
Automatic speaker diarization (who said what)
Real-time, speaker-diarized transcription with low latency
Team usage
AI summaries with custom prompts via Ollama or OpenAI-compatible providers
Deployable bots that join meetings via URL to capture audio
Integrations
Chat with your transcripts to ask questions and pull insights
Open-source (Apache 2.0) with self-hosted or managed cloud options
Languages & capture
Built-in audio recorder and note-taking on transcripts
Data storage with query and export capabilities
Best-fit workflow
Folder watcher and API endpoints for automation workflows
Supports Google Meet and Microsoft Teams (Zoom planned)
Best for
Scriberr
Choose Scriberr if you need privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure — strengths include fully self-hosted and offline, keeping audio and transcripts on your own hardware.
Vexa
Choose Vexa if you need building custom meeting-intelligence features into a product — strengths include programmable infrastructure for embedding meeting transcription into products.
Pros & cons
Scriberr
+ Fully self-hosted and offline, keeping audio and transcripts on your own hardware
+ MIT-licensed and free to run with no per-minute charges
- Active development was publicly paused by the maintainer, relying on community contributions
Vexa
+ Programmable infrastructure for embedding meeting transcription into products
+ Open-source and self-hostable for control over data and deployment
- Developer-oriented rather than a ready-to-use end-user notetaking app
FAQ
Is Scriberr or Vexa better for AI meeting notes?
It depends on your workflow. Scriberr is strong for privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure, while Vexa is strong for building custom meeting-intelligence features into a product. Both transcribe and summarize meetings.
How do Scriberr and Vexa compare on price?
Scriberr is a free tier with paid upgrades and Vexa 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 Scriberr and Vexa?
Yes. Many teams run more than one meeting assistant when the workflows are complementary and the budget is justified.