Turn meetings into execution — inside your workflow, on-prem.
Aide is a comprehensive AI agent designed to improve work efficiency, reduce time and resource costs, and make daily work clear and organized. Not another note-taker — Aide is a workflow-native execution layer with governed enterprise memory that answers the four questions every team asks later: Why? Where? Who? What next?
Teams waste hours every week reconstructing "why / who / what next" — and policy often forbids cloud recording. This creates:
- Decision drift — Decisions are made, but their context is lost quickly
- Ownership gaps — Unclear who is responsible for what after meetings
- Follow-up loss — Action items fail to be reliably captured or transferred into tools like Jira, CRM, or email
- Cross-team amnesia — New team members struggle to understand past decisions and their rationale
The cost: Repeated meetings, manual notes + status chasing + documentation overhead, slow onboarding, painful handoffs across teams, and higher audit and compliance friction.
Why existing tools fail:
- Cloud-first tools are blocked by policy due to sensitive conversations
- Many "meeting bots" introduce security/compliance friction, leading to slow adoption
- Tools produce notes, not workflow execution + governed memory
Decisions + context + owners + approvals are always traceable. Every meeting decision is automatically captured with full context, making it easy to answer "Where was this decided — and who approved it?"
Action items with deadlines/status are not merely recorded — they're pushed into Jira/Slack/Email/CRM (coming soon). Aide transforms meeting discussions into actionable workflow items.
Cross-meeting search answers "why/who/what next" questions in seconds. Aide maintains a comprehensive knowledge base across all your meetings, making historical context instantly accessible.
Run Aide with local embedded engines or a self-hosted unified HTTP backend. No third-party cloud dependency is required.
- Live audio transcription with low latency (<200ms)
- Frame-based streaming with automatic commit detection
- Voice Activity Detection with intelligent buffering
- Support for system audio and microphone
- File upload transcription for recorded meetings
- AI-powered meeting summaries with structured output
- Executive summary, key topics, decisions, and action items
- Streaming token generation for real-time feedback
- Metal GPU acceleration on Apple Silicon
- Powered by local Llama.cpp inference
- Role-based meeting agents for Sales, Engineering, Legal, and Management
- Chat UI with tool-grounded answers
- Natural language query interface
- Shared Enterprise Memory — agents leverage cross-meeting knowledge
- Cross-agent search for comprehensive insights
- Full-text search across all meeting transcripts and summaries
- Smart filtering by date, duration, status, tags, and metadata
- BM25 ranking algorithm for relevant results
- Highlighted match snippets with context
- Cross-meeting search to answer "why/who/what next" questions
- Automatic calendar access with permission management
- View upcoming events and meetings
- Create calendar events directly from the agent
- Seamless workflow integration
- Local or self-hosted processing — no third-party cloud dependency required
- Policy, Permissions & Audit — built-in governance and traceability
- On-premise deployment ready
- No account or internet required (after model download)
- Full user control over data
Aide is built on three foundational technologies:
- Local embedded mode: whisper-based native runtime
- Remote mode: unified Aide AI server (
/v1/asr/transcriptions+ streaming APIs) - Real-time transcription with low latency
- Support for multiple audio sources
- Local embedded mode: llama-based native runtime
- Remote mode: unified Aide AI server (
/v1/summaries,/v1/chat/completions) - Summarization, action item extraction, and agent reasoning
- Context + output guardrails for stable memory usage
- Built-in security and governance features
- Permission management for calendar and microphone
- Audit trail for all meeting data
- Compliance-ready architecture
- 🔀 Unified backend mode switch — one setting controls ASR + LLM transport (
Local EmbeddedvsRemote HTTP Server) - 🌐 Remote backend UI panel — base URL, API key, and health-check in
Settings > AI Backend - 🟢 Global engine status indicator — app-wide readiness icon for local/remote engines
- 🚫 No silent fallback in remote mode — tasks fail fast with explicit configuration errors
- 🎙️ Remote realtime streaming — app now supports server-side streaming ASR endpoints
- 🧾 Operational logging split — server routes concise logs to console, detailed logs to
server.log/engine.log
# Download the appropriate DMG for your Mac:
# Apple Silicon (M1/M2/M3/M4): aide_macos_arm64_1.6.3.dmg
# Intel: aide_macos_x86_64_1.6.3.dmg
# Open DMG and drag to Applications
open aide_macos_arm64_1.6.3.dmg# Download aide_windows_x64_1.6.3.zip
# Extract and run asr_app.exeFirst Launch:
- Grant microphone and calendar permissions (auto-requested)
- Models download automatically (~2.5 GB, 5-10 minutes)
- Start recording or upload audio files!
# Clone repository
git clone <repo-url>
cd ASREngine/asr_app
# Get dependencies
flutter pub get
# Run in debug mode
flutter runRequirements:
- Flutter SDK 3.24+
- macOS: Xcode 15+
- Windows: Visual Studio 2022 + C++ workload
| Document | Description |
|---|---|
| USAGE.md | End-user manual & guide |
| aide-ai-platform/README.md | Unified ASR+LLM server deployment |
| AI HTTP Server (Dev) | Server setup, API usage, tuning, and troubleshooting |
| SERVER_TECHNICAL.md | Server runtime architecture and APIs |
| GETTING_STARTED.md | Complete setup guide for developers |
| BUILD.md | Build instructions for macOS & Windows |
| MODELS.md | Model management and configuration |
| ARCHITECTURE.md | Technical deep dive: FFI, dylibs, Metal |
| API_STREAM.md | Streaming engine C API reference |
| TROUBLESHOOTING.md | Common issues and solutions |
Aide Desktop App (Flutter)
↓ (Dart FFI)
Native Helper Libraries
↓ (C++ Inference)
whisper.cpp / llama.cpp
↓ (GPU Acceleration)
Metal / CoreML (Apple Silicon)
- libstream.dylib - C++ streaming engine with frame-based API
- whisper.cpp - ASR inference engine with Metal acceleration
- llama.cpp - LLM inference engine for summarization and agent reasoning
- Silero VAD - Voice activity detection
- ScreenCaptureKit - System audio capture (macOS)
- Flutter - Cross-platform UI framework
- Tool Orchestrator - Agent tool system for SEARCH, LIST_HISTORY, MEETING_DETAILS, CALENDAR_GET
~/.Aide/
├── models/ # AI models (~2.5 GB)
│ ├── ggml-distill_lv3.bin # ASR model
│ └── Qwen3-0.6B-Q8_0.gguf # LLM model
├── history/ # Session data
│ ├── aide.db # SQLite database
│ └── sessions/ # Individual session data
│ └── <session_id>/
│ ├── audio.wav # Original recording
│ ├── transcript.txt # Segmented text
│ ├── timestamp.bin # Binary timestamps (Int64 pairs)
│ ├── metadata.bin # Segment count (Int32)
│ └── summary.md # AI Summary
└── logs/ # Application logs (if enabled)
cd asr_app
bash build_release.shOutput: Aide-x.x.x-macos.dmg (signed and notarized)
Features:
- Code signing with Developer ID
- Notarization for Gatekeeper
- Professional DMG with drag-to-install
- Automatic retries for reliability
cd asr_app
bash build_release_windows.shOutput: Aide-x.x.x-windows-x64.zip
Optional installer:
bash build_release_windows.sh --installerSee BUILD.md for detailed instructions.
- 📝 Transcribe meetings, interviews, lectures with instant results
- 🎤 Record voice memos with automatic transcription
- 📊 Generate meeting summaries automatically (Pro)
- 🔍 Search through conversation history to find past decisions (Pro)
- 🤖 Get AI-powered insights and action items (Pro)
- 💼 Internal meetings and brainstorming sessions
- 🎓 Training sessions and workshops
- 📞 Client calls (with permission)
- 🗣️ Standup meetings and retrospectives
- 🔄 Decision trail tracking — Always know where decisions were made
- 👥 Ownership clarity — Track who approved what and when
- ✅ Action item execution — Transform discussions into workflow items
- 🏢 Regulated organizations — On-premise deployment with full audit trail
- 🔒 Security-sensitive environments — No cloud, no data leaks
- 📋 Compliance requirements — Built-in governance and traceability
- 🔍 Cross-team knowledge — Shared enterprise memory across departments
- 🎯 Workflow integration — Connect to Jira, Slack, CRM (coming soon)
- 🎙️ Podcast transcription
- 📹 Video content planning
- ✍️ Blog post drafts from voice notes
- 🎬 Interview transcription
- ❌ No cloud processing
- ❌ No data collection
- ❌ No telemetry or analytics
- ❌ No account required
- ❌ No internet connection needed (after setup)
- ❌ No third-party services
- ✅ 100% local AI inference
- ✅ Data stored only on your device
- ✅ Open-source components (whisper.cpp, llama.cpp)
- ✅ Transparent architecture
- ✅ Full user control over data
- ✅ On-premise ready
- ✅ Enterprise-grade security
| Metric | Value |
|---|---|
| Transcription Latency | <200ms |
| Real-time Factor (RTF) | ~0.1x (10x faster than real-time) |
| Model Size | ASR: 1.5 GB, LLM: 1 GB |
| Memory Usage | ~2-3 GB during active use |
| GPU Acceleration | 5-10x speedup on Apple Silicon |
| App Size | ~50 MB (models downloaded separately) |
| Context Window | 32k tokens (with intelligent truncation) |
| Component | Technology |
|---|---|
| UI Framework | Flutter 3.24+ |
| ASR Engine | whisper.cpp |
| LLM Engine | llama.cpp |
| VAD | Silero VAD |
| GPU | Metal (macOS), DirectML (Windows planned) |
| Database | SQLite |
| Search | BM25 ranking algorithm |
| Audio | dart_soundboard, ScreenCaptureKit |
| Agent Tools | Custom tool orchestrator with EXECUTE protocol |
We welcome contributions! Here's how:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
See GETTING_STARTED.md for complete setup instructions.
See LICENSE file for details.
Built with amazing open-source projects:
- Flutter - UI framework
- whisper.cpp - ASR engine
- llama.cpp - LLM engine
- Silero VAD - Voice activity detection
- Hugging Face - Model hosting
AI Models:
- 📖 Documentation: Check
docs/folder - 🐛 Issues: GitHub Issues
- 💬 Discussions: GitHub Discussions
- ✅ Real-time transcription
- ✅ AI summarization (Pro)
- ✅ Advanced search (Pro)
- ✅ AI Agent Assistant (Pro)
- ✅ Session history
- ✅ Calendar integration
- ✅ macOS & Windows support
- ✅ Dark/Light themes
- 🔄 Workflow connectors (Jira, Slack, Teams, Zoom, CRM)
- 📤 Export to multiple formats
- 🎨 Custom themes
- 🌐 Multi-language UI
- 🔄 Auto-update system
- 🗣️ Speaker diarization
- 📊 Advanced analytics and insights
- 🔌 Plugin system
- 🐧 Linux support
- 🌍 Multi-language transcription
- 📈 Team collaboration features
Not another note-taker — Aide is a workflow-native execution layer with governed enterprise memory. Aide answers the four questions every team asks later:
- Why? — Decision trail with full context
- Where? — Cross-meeting search finds where decisions were made
- Who? — Ownership tracking and approval records
- What next? — Action items pushed into workflow tools
On-premise & privacy-first — Perfect for enterprises that need security without sacrificing functionality.
Execution, not notes — Transform meeting discussions into actionable workflow items, not just passive documentation.
Made with ❤️ for teams that value privacy, efficiency, and execution
No cloud. No data leaks. Just you, your AI, and your workflow.