Hyperia and Speakr are both AI meeting assistants for recording, transcription, and summaries, compared here on pricing, features, and workflow fit. Hyperia: A programmable AI notetaker that joins online meetings as a participant to record, transcribe, and build searchable knowledge from conversations. Speakr: Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search. 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 Hyperia when automatically capturing and summarizing recurring team or client calls matters most, and Speakr when privacy-conscious teams self-hosting transcription and summaries for internal meetings matters most. Both record across Zoom, Google Meet, and Microsoft Teams; trial each on real meetings before committing.
A programmable AI notetaker that joins online meetings as a participant to record, transcribe, and build searchable knowledge from conversations.
Automatic calendar detection and joining of scheduled meetingsCRM and SaaS integrations, including via ZapierNotetaker joins Zoom, Microsoft Teams, and Google Meet as a participant
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
Hyperia is a free tier with paid upgrades (freemium); Speakr is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
Notetaker joins Zoom, Microsoft Teams, and Google Meet as a participant
Self-hosted transcription with automatic language detection
Standout feature
Automatic calendar detection and joining of scheduled meetings
Optional AI-powered speaker diarization
Team usage
Programmable API to direct the notetaker and stream audio for analysis
Customizable summaries plus an action-items view for decisions and tasks
Integrations
Transcription, summaries, action items, and highlights
Per-recording chat and an Inquire Mode for semantic search across the whole library
Languages & capture
Searchable knowledge base built from calls and meetings
System and browser-tab audio capture
Best-fit workflow
CRM and SaaS integrations, including via Zapier
Multi-user support with SSO, group workspaces, and admin dashboard
Best for
Hyperia
Choose Hyperia if you need automatically capturing and summarizing recurring team or client calls — strengths include programmable api offers flexibility for custom workflows and integrations.
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.
Pros & cons
Hyperia
+ Programmable API offers flexibility for custom workflows and integrations
+ Turns meetings into a searchable knowledge base across conversations
- Notetaker joins as a visible participant rather than operating bot-free
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
FAQ
Is Hyperia or Speakr better for AI meeting notes?
It depends on your workflow. Hyperia is strong for automatically capturing and summarizing recurring team or client calls, while Speakr is strong for privacy-conscious teams self-hosting transcription and summaries for internal meetings. Both transcribe and summarize meetings.
How do Hyperia and Speakr compare on price?
Hyperia is a free tier with paid upgrades and Speakr 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 Hyperia and Speakr?
Yes. Many teams run more than one meeting assistant when the workflows are complementary and the budget is justified.