stenoai
Privacy focused AI powered meeting notes using locally hosted Small Language Models
Stars: 279
StenoAI is an AI-powered meeting intelligence tool that allows users to record, transcribe, summarize, and query meetings using local AI models. It prioritizes privacy by processing data entirely on the user's device. The tool offers multiple AI models optimized for different use cases, making it ideal for healthcare, legal, and finance professionals with confidential data needs. StenoAI also features a macOS desktop app with a user-friendly interface, making it convenient for users to access its functionalities. The project is open-source and not affiliated with any specific company, emphasizing its focus on meeting-notes productivity and community collaboration.
README:
AI-powered meeting intelligence that runs entirely on your device, your private data never leaves anywhere. Record, transcribe, summarize, and query your meetings using local AI models. Perfect for healthcare, legal and finance professionals with confidential data needs.
Trusted by users at AWS, Deliveroo & Tesco.
Disclaimer: This is an independent open-source project for meeting-notes productivity and is not affiliated with, endorsed by, or associated with any similarly named company.
- Local transcription using whisper.cpp
- AI summarization with Ollama models
- Ask Steno - Query your meetings with natural language questions
- Multiple AI models - Choose from 4 models optimized for different use cases
- Privacy-first - 100% local processing, your data never leaves your device
- macOS desktop app with intuitive interface
Have questions or suggestions? Join our Discord to chat with the community.
Transcription Models (Whisper):
-
small: Default model - good accuracy and speed on Apple Silicon (default) -
base: Faster but lower accuracy for basic meetings -
medium: High accuracy for important meetings (slower)
Summarization Models (Ollama):
-
llama3.2:3b(2GB): Fastest option for quick meetings (default) -
gemma3:4b(2.5GB): Lightweight and efficient -
qwen3:8b(4.7GB): Excellent at structured output and action items -
deepseek-r1:8b(4.7GB): Strong reasoning and analysis capabilities
Switching Models:
- Click the 🧠 AI Settings icon in the app
- Select your preferred model
- Models download automatically when selected
⚠️ Note: Downloads will pause any active summarization
- Custom summarization templates
- Speaker Diarisation
Download the latest release for your Mac:
- Apple Silicon (M1/M2/M3/M4)
- Intel Macs Performance on Intel Macs is limited due to lack of dedicated AI inference capabilities on these older chips.
-
Download and open the DMG file
-
Drag the app to Applications
-
When you first launch the app, macOS may show a security warning
-
To fix this warning:
- Go to System Settings > Privacy & Security and click "Open Anyway"
Alternatively:
- Right-click StenoAI in Applications and select "Open"
- Or run in Terminal:
xattr -cr /Applications/StenoAI.app
-
The app will work normally on subsequent launches
You can run it locally as well (see below) if you dont want to install a dmg.
- Python 3.9+
- Node.js 18+
git clone https://github.com/ruzin/stenoai.git
cd stenoai
# Backend setup
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Download bundled binaries (Ollama, ffmpeg)
./scripts/download-ollama.sh
# Build the Python backend
pip install pyinstaller
pyinstaller stenoai.spec --noconfirm
# Frontend
cd app
npm install
npm startNote: Ollama and ffmpeg are bundled - no system installation needed. The setup wizard in the app will download the required AI models automatically.
cd app
npm run buildcd app
# Patch release (bug fixes): 0.0.5 → 0.0.6
npm version patch
git add package.json package-lock.json
git commit -m "Version bump to $(node -p "require('./package.json').version")"
git push
git tag v$(node -p "require('./package.json').version")
git push origin v$(node -p "require('./package.json').version")
# Minor release (new features): 0.0.6 → 0.1.0
npm version minor
git add package.json package-lock.json
git commit -m "Version bump to $(node -p "require('./package.json').version")"
git push
git tag v$(node -p "require('./package.json').version")
git push origin v$(node -p "require('./package.json').version")
# Major release (breaking changes): 0.0.6 → 1.0.0
npm version major
git add package.json package-lock.json
git commit -m "Version bump to $(node -p "require('./package.json').version")"
git push
git tag v$(node -p "require('./package.json').version")
git push origin v$(node -p "require('./package.json').version")What happens:
-
npm versionupdates package.json and package-lock.json locally - Manual commit ensures version changes are saved to git
-
git pushsends the version commit to GitHub -
git tagcreates the version tag locally -
git push origin tagtriggers GitHub Actions workflow - Workflow automatically builds DMGs for Intel & Apple Silicon
- Creates GitHub release with downloadable assets
stenoai/
├── app/ # Electron desktop app
├── src/ # Python backend
├── website/ # Marketing site
├── recordings/ # Audio files
├── transcripts/ # Text output
└── output/ # Summaries
StenoAI includes a built-in debug panel for troubleshooting issues:
In-App Debug Panel:
- Launch StenoAI
- Click the 🔨 hammer icon (next to settings)
- The debug panel shows real-time logs of all operations
Terminal Logging (Advanced): For detailed system-level logs, run the app from Terminal:
# Launch StenoAI with full logging
/Applications/StenoAI.app/Contents/MacOS/StenoAIThis displays comprehensive logs including:
- Python subprocess output
- Whisper transcription details
- Ollama API communication
- HTTP requests and responses
- Error stack traces
- Performance timing
System Console Logs: For system-level debugging:
# View recent StenoAI-related logs
log show --last 10m --predicate 'process CONTAINS "StenoAI" OR eventMessage CONTAINS "ollama"' --info
# Monitor live logs
log stream --predicate 'eventMessage CONTAINS "ollama" OR process CONTAINS "StenoAI"' --level infoCommon Issues:
- Recording stops early: Check microphone permissions and available disk space
- "Processing failed": Usually Ollama service or model issues - check terminal logs
- Empty transcripts: Whisper couldn't detect speech - verify audio input levels
- Slow processing: Normal for longer recordings - Ollama processing is CPU-intensive especially on older intel Macs
-
User Data:
~/Library/Application Support/stenoai/ -
Recordings:
~/Library/Application Support/stenoai/recordings/ -
Transcripts:
~/Library/Application Support/stenoai/transcripts/ -
Summaries:
~/Library/Application Support/stenoai/output/
This project is licensed under the MIT License.
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