Rychagov S.
🎙️ Whisper · LLM

AI Meeting Transcription

Records meetings, transcribes speech, and identifies speakers with fully local processing on your own hardware — no data is sent to external services, ensuring complete confidentiality.

Key facts

Processing mode

Fully local transcription on your hardware, with no data sent to external services.

Languages and speakers

50+ languages, automatic language detection, and speaker diarization.

Outputs

Transcript, summary, action items, and quick jump-to-timestamp navigation.

Platforms

Desktop app for macOS and Windows, with Linux in beta.

FAQ

Can it run fully offline?

Yes, local transcription works offline; internet is only needed for optional external LLM usage.

Which audio sources are supported?

System audio and microphone can be captured simultaneously for transcription.

How fast is result generation?

It depends on hardware and recording length, typically available right after processing.

How is confidentiality ensured?

In local mode, data stays inside your infrastructure and is not sent to external APIs.

Limitations and when it may not fit

On low-spec hardware, transcription speed can be slower than real-time.

Recognition quality decreases when source audio quality is poor.

Domain-specific terminology may require custom vocabulary and model tuning.

Desktop application

💻

Download the app

Install the app for your OS and start recording meetings in minutes.

🔒

Local transcription and privacy

Audio is processed locally on your device without sending data to external services. Recordings and transcripts stay within your infrastructure.

The problem: you forget 80% of what was discussed

Manual note-taking distracts from the conversation. An hour after the call, context starts fading. Teams spend hours writing follow-up emails and recounting decisions.

Decisions get lost in chat threads and never make it into the company knowledge base — every meeting starts from scratch.

How it works

1

Recording

The app captures system audio and microphone in high quality. One click — and recording begins.

2

Transcription

Whisper instantly converts speech to text with 50+ language support. Automatically identifies speakers.

3

AI Analysis

LLM extracts key decisions, creates a structured summary, and generates a task list with assignees.

4

Knowledge base

All meetings are saved with full-text search. Click any phrase to jump to that moment in the recording.

Example output

[00:12] Speaker 1: We need to update the homepage design by next Tuesday...

[00:45] Speaker 2: Agreed. I'll prepare Figma prototypes by Friday evening.

[01:20] Speaker 1: Great. Don't forget about the mobile version too.

AI Summary

✅ Homepage design — update UI by October 14.

✅ Figma prototypes — assignee: Speaker 2. Deadline: Friday.

✅ Mobile version — include in the current sprint as a priority.

Features

🎙️

Recording

System audio + microphone in high quality (WAV/MP3). Runs in the background.

🌐

50+ languages

Automatic language detection and speaker diarization.

AI Summary

Key decisions, insights, and action items with assignees — automatically.

🖥️

Local LLM

Ollama integration for local processing. Your data never leaves your machine.

🗂️

Meeting history

Full-text search across all past meetings with jump-to-timestamp navigation.

Quick navigation

Click any phrase in the transcript — the player jumps right to that moment.

Platforms

Desktop app for macOS M1/M2/M3, Windows 10/11, and Linux (Beta). Works offline — internet is only needed for cloud LLM models.

Want to discuss practical AI meeting transcription?

I can share proven patterns, limitations, and what actually improves outcomes for teams.

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