StenoAI is the privacy-first AI notepad for all your confidential conversations. No cloud, no usage limits and your private data never leaves your premises. Record, summarize, and query your meetings using local AI models. Perfect for government, defence and C-suite professionals with confidential data needs.

_{Trusted by teams at AWS, Deliveroo, Tesco, Hashicorp, Rutgers & European Union.}

_{Sponsored by Gitlab Founder's Open Core Ventures.}

_{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.}

Sponsors

Recall.ai - API for desktop recording

If you're looking for a hosted desktop recording API, consider checking out Recall.ai, an API that records Zoom, Google Meet, Microsoft Teams, in-person meetings, and more.

📢 What's New

• 2026-09-05 🐧 Linux alpha: Debian/Ubuntu packages and an AppImage support microphone and PipeWire system-audio recording, with CPU-only bundled summaries.
• 2026-09-05 📁 Reliable recording and folders: failed recording starts no longer leave a stuck entry, and repeated clicks no longer create duplicate folders.
• 2026-09-05 📥 Clear download progress: Parakeet shows actual download progress and a separate model-preparation stage.
• 2026-09-05 📝 Transcript recovery: on Windows and Linux, the available live transcript replaces an ONNX batch transcript that read less than half the recording.

Features

• Privacy-first: local AI processes your recordings, transcripts, and summaries on your device. External AI providers are optional.
• Live speaker labels — Real-time on-screen text as you speak via Parakeet TDT v3 on Apple Silicon (MLX). Granola-style chat-bubble view with [You] vs [Others] attribution live during the recording.
• Individual speakers (macOS) — Once the recording stops, Steno separates the voices sharing each channel, so the saved transcript reads Speaker 2 / Speaker 3 rather than one merged [Others]. Name a speaker once and Steno can suggest them in later meetings — that part is off by default, and the voice profiles never leave your Mac.
• Auto start/stop meetings — Steno notices when a meeting starts and offers to take notes, then offers to summarise when it ends. Granola-style frictionless capture.
• System audio capture — Record both sides of virtual meetings. Native Core Audio Tap on macOS 14.4+, Windows loopback capture, and PipeWire capture on Linux, with selectable microphone input.
• Recording that coexists — A compact transcription pill docks beside the app instead of taking over; Stop lands you on the note instantly and you can resume recording into an existing note (it appends and re-generates on demand).
• Global record shortcut — Start or stop recording from anywhere with ⌘⇧R (Ctrl+Shift+R on Windows). Toggle it off in Settings if it clashes with another app. On macOS, power users can additionally bind any key of their own via the stenoai://record/start / record/stop deep links (Shortcuts app).
• In-app note-taking — Jot notes while you record, or keep a dedicated My notes tab that stays editable alongside the AI summary; your notes are folded straight into the summary.
• Ask your meetings — Natural-language Q&A across a single note or your entire library via the Chat tab. Pulls from summary, key topics, and the full transcript.
• Multi-language (25 live, 99 total) — Parakeet covers 25 European languages with live transcription; Whisper handles 99 languages including Chinese, Japanese, Arabic, and Hindi post-stop.
• Markdown ownership — Summaries and transcripts save as clean Markdown you can edit, search, or sync to whatever knowledge base you live in.
• Report templates — Define custom report styles and generate them per meeting; a note can hold multiple reports (the structured summary plus template-driven ones), switchable in the detail view.
• Transcript export — Copy the full transcript or save it as Markdown (with metadata, notes, and speaker labels) to drop into any external tool.
• Bring your own cloud model — Optional OpenAI, Anthropic, AWS Bedrock (Claude — including application inference profile ARNs for governed AWS environments), or custom API endpoint for users who prefer a hosted LLM.
• Organisation AI — On managed deployments, sign in to your org's Steno adapter and AI routes through it automatically — no local API key, no per-user setup.

Coming from Granola?

If you already use Claude Code / Cowork with a connected Granola MCP, the granola-to-steno skill syncs your Granola meeting notes (titles, dates, participants, summaries, and transcripts) into Steno's file-based store. It is idempotent and re-runnable, so you can backfill your history once and keep it in sync on a schedule. This is an agent skill you drop into your skills folder and invoke conversationally ("sync Granola to Steno"), not an in-app feature. See skills/granola-to-steno/README.md for setup and limitations.

Use your notes from an agent (/steno)

The steno skill makes an AI agent aware of your local Steno notes. Run /steno (or just mention your meetings) and it pulls in the relevant notes and acts on them — answer a question across meetings, recap your week, extract action items, or use the meetings as source material to draft a spec, PRD, or follow-up. It can also guide you through setting up a cloud model (/steno setup) — OpenAI, Anthropic, AWS Bedrock, or a custom endpoint.

It's read-only over your notes (never modifies them), needs only Python 3.8+ (no dependencies), and is a drop-in agent skill — copy skills/steno/ into your skills folder. See skills/steno/README.md.

macOS Shortcuts (Optional)

Expand setup and calendar automation guide

Steno supports Apple Shortcuts via deep links using the stenoai:// URL scheme.

• Start recording: stenoai://record/start?name=Daily%20Standup
• Stop recording: stenoai://record/stop

How to set it up

1. Open the Shortcuts app on macOS.
2. Create a new shortcut (for example: "Start Steno Recording").
3. Add the Open URLs action.
4. Use one of the URLs above.
5. (Optional) Add a keyboard shortcut from the shortcut settings.

Calendar event naming (optional)

If you want calendar-based names, resolve the event title in your Shortcut workflow and pass it as the name query value in the start URL.

Example:

stenoai://record/start?name=Weekly%20Product%20Sync

Calendar event start automation (via Rules bridge)

macOS Shortcuts cannot natively trigger exactly at Calendar event start.
To run this automatically on event timing, a third-party automation app is required.

This addon uses:

• Apple Shortcuts: builds the stenoai://record/start?... action.
• Rules – Calendar Automation: watches Calendar events and triggers the shortcut.

Architecture overview

1. Rules App monitors upcoming Calendar events.
2. Rules checks the event note/body for a marker keyword (for example stenoai).
3. If matched, Rules runs a Shortcut.
4. The Shortcut gets the next event title and opens:
   • stenoai://record/start?name={calendar_event_title}
5. Steno receives the URL and starts recording with that name.

Step-by-step setup

1. Install Rules – Calendar Automation on macOS.
2. Create a Shortcut in Apple Shortcuts (example name: Steno Start From Calendar Event).
3. In that Shortcut, add actions in this order:
   • Find Calendar Events (limit to 1, sorted by start date ascending, upcoming only)
   • Extract the event title from the found event
   • URL Encode the title
   • Open URLs with:
     • stenoai://record/start?name=<encoded title>
4. Open Rules and create a calendar-trigger rule:
   • Source: your target calendar(s)
   • Trigger window: event start (or preferred offset)
   • Condition: event note contains stenoai
   • Action: run Shortcut Steno Start From Calendar
5. In your Calendar event notes, add the word stenoai for meetings that should auto-start recording.
6. Test with a near-future event:
   • create event with stenoai in notes,
   • wait for trigger,
   • confirm Steno starts and uses the event title as session name.

Notes

• Without Rules (or another automation bridge), this cannot be fully event-driven from Calendar start time.
• Keep using regular manual shortcuts (Open URLs) for non-automated scenarios.

Have questions or suggestions? Join our Discord to chat with the community.

Models & Performance

Transcription Models:

• Parakeet TDT v3 (572 MB): Highest quality, supports live transcription, 25 European languages (English, Spanish, French, German, Italian, Portuguese, Dutch, Russian, Polish, Czech, and 15 others). Apple Silicon only via MLX. (default on fresh installs)
• Whisper Large V3 Turbo (1.6 GB): Best-accuracy Whisper engine for the languages Parakeet can't speak (Chinese, Japanese, Korean, Arabic, Hindi, and 94 others). Post-stop only.

Summarization Models (Ollama):

• gemma4:e2b-it-qat (4.3GB): Lightest Gemma 4, quantization-aware, with a real 128K context (default)
• gemma4:e4b-it-qat (6.1GB): Quantization-aware E4B — higher quality than E2B at a modest footprint
• qwen3.5:9b (6.6GB): Excellent at structured output and action items
• gemma4:12b-it-qat (7.2GB): Gemma 4 (quantization-aware) with a 256K context — best for long meetings
• gpt-oss:20b (14GB): OpenAI open-weight model with reasoning capabilities

Future Roadmap

Enhanced Features

• Windows: GA hardening (alpha already ships on Windows 10/11 x64)

Installation

Download the latest release (Apple Silicon Mac, macOS 14.4 or later):

• Apple Silicon (M1-M5)

Intel Mac users: v0.4.0 is Apple Silicon only. Stay on v0.3.8 — the last release supporting Intel Macs. Auto-update on existing Intel installs will not push v0.4.0 to those machines.

Installing on macOS

1. Download and open the DMG file

2. Drag the app to Applications

3. When you first launch the app, macOS may show a security warning

4. To fix this warning:

   • Go to System Settings > Privacy & Security and click "Open Anyway"

   Alternatively:

   • Right-click Steno in Applications and select "Open"
   • Or run in Terminal: xattr -cr /Applications/Steno.app

5. The app will work normally on subsequent launches

You can run it locally as well (see below) if you don't want to install a DMG.

Windows (alpha)

Windows 10/11 (x64) is supported in alpha, with the full pipeline verified working: record → live Parakeet transcription → batch transcript → Ollama summary, including system-audio loopback capture with [You]/[Others] diarisation.

Install: download stenoAI-windows-x64.exe from the latest release and run it — it installs per-user (no admin needed) and creates Start-menu/desktop shortcuts. On first launch, Windows SmartScreen warns because the alpha is unsigned — click More info → Run anyway. The first-run setup wizard then downloads the transcription model (~670 MB) and the default summarisation model, Gemma 4 E2B (~4.3 GB).

Before the first tagged Windows release lands, grab the installer from the Windows build workflow: sign in to GitHub, open the latest green run, download the stenoai-windows artifact, and run the .exe inside.

Known alpha limitations:

• Unsigned — SmartScreen warns on first launch; we'll code-sign before 1.0.
• CPU-only summarisation — the bundled Ollama runs on CPU (the NVIDIA GPU libraries are excluded to keep the download small); a separate GPU build is a follow-up. Transcription is CPU on every platform regardless.
• Auto-update is wired (NSIS + latest.yml) but updates are unsigned until code signing is in place.
• Transcription runs through onnx-asr (ONNX Runtime) instead of MLX, with the same Parakeet model and behaviour as macOS. Whisper is also available as an engine option.

Linux (Debian/Ubuntu, alpha)

Verified on Ubuntu 26.04 LTS (GNOME/Wayland, PipeWire), including system-audio loopback capture with [You]/[Others] diarisation.

Install (.deb, recommended): download stenoAI-linux-amd64.deb from the latest release and install it with sudo apt install ./stenoAI-linux-amd64.deb — apt pulls in the required system libraries automatically.

AppImage: download stenoAI-linux-x86_64.AppImage, chmod +x it, and run it. An AppImage carries no package metadata, so you must install PortAudio yourself or the setup check fails with OSError: PortAudio library not found:

sudo apt install libportaudio2

Known alpha limitations:

• Unsigned, same as the Windows alpha.
• CPU-only bundled summarisation and onnx-asr transcription, same as Windows. To use GPU-accelerated summaries, run a separately installed Ollama with a supported GPU and driver, select Settings → AI → Private Server, enter http://127.0.0.1:11434, and choose a model installed on that server.
• System audio requires PipeWire (Ubuntu's default since 22.10). The toggle reports unsupported on a PulseAudio-only or headless install, and recording falls back to mic-only.
• No speaker diarization sidecar — per-channel [You]/[Others] labelling works, but the acoustic multi-speaker split is macOS-only.
• No auto-update. .deb installs update by downloading a new package; AppImage self-update is a follow-up.

Issues + feedback welcome on the GitHub issues tracker.

Local Development/Use Locally

Prerequisites

• Python 3.9+
• Node.js 18+

Setup

git clone https://github.com/stenolabs/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 start

Note: Ollama and ffmpeg are bundled - no system installation needed. The setup wizard in the app will download the required AI models automatically.

Build

cd app
npm run build

Project Structure

stenoai/
├── app/                  # Electron desktop app
├── src/                  # Python backend
├── website/              # Marketing site
├── recordings/           # Audio files
├── transcripts/          # Text output
└── output/              # Summaries

Troubleshooting

Debug Logs

Setup wizard debug console: during first-time setup, expand the debug console panel to see real-time logs of model downloads and service startup.

Terminal logging (recommended for runtime issues): launch the app from a terminal to stream all logs (Python subprocess output, Whisper transcription, Ollama API traffic, error stack traces):

/Applications/Steno.app/Contents/MacOS/Steno

System Console:

# View recent Steno-related logs
log show --last 10m --predicate 'process CONTAINS "Steno" OR eventMessage CONTAINS "ollama"' --info

# Monitor live logs
log stream --predicate 'eventMessage CONTAINS "ollama" OR process CONTAINS "Steno"' --level info

Common Issues

• Update didn't install: Auto-updates are applied on next quit. Quit via the Steno → Quit menu (not just closing the window), then reopen.
• No system audio / no [Others] speaker labels: On macOS, allow Steno to record system audio in System Settings → Privacy & Security → Screen & System Audio Recording. Screen Recording access is not required.
• stenoai:// deep link doesn't start recording: Make sure Steno has launched at least once after install so the URL scheme is registered. If it still fails, check the terminal log for Protocol handler registration output.
• Recording stops early: Check microphone permission, System Audio Recording permission (if recording system audio), and available disk space.
• "Processing failed": Usually an Ollama service or model issue — check the terminal logs.
• Empty transcripts: Whisper couldn't detect speech — verify audio input levels.
• Slow processing: Normal for longer recordings; Ollama is CPU-intensive. If summaries are unusually slow, switch to a lighter model in Settings → AI (Gemma 4 E2B is the lightest/fastest).

Logs Location

• User Data: ~/Library/Application Support/stenoai/
• Recordings: ~/Library/Application Support/stenoai/recordings/
• Transcripts: ~/Library/Application Support/stenoai/transcripts/
• Summaries: ~/Library/Application Support/stenoai/output/

License

This project is licensed under the MIT License.