At a Glance:
Meetily is a privacy-first, open-source AI meeting assistant that captures, transcribes, and summarizes meetings entirely on a user's local machine; it supports local Whisper and Parakeet models, real-time transcription, and flexible AI providers including Ollama, Claude, and custom OpenAI-compatible endpoints.
Overview:
Meetily is a local-first AI meeting assistant designed for professionals who require complete data sovereignty over their meeting transcripts and summaries. It captures system and microphone audio, performs real-time transcription using locally-run speech-to-text models like Whisper or Parakeet, and generates AI-powered summaries. All processing stays on the user's device, with no cloud data transmission. The application is a self-contained, cross-platform desktop tool built with Tauri, supporting macOS, Windows, and Linux. It offers flexible AI backend options, allowing users to switch between fully local models via Ollama, or connect to cloud providers like Claude, Groq, OpenRouter, and custom OpenAI-compatible endpoints. A free, community edition is maintained alongside a separate, commercial PRO version with enhanced accuracy and team-oriented features.
Key Decision Points:
Complete data sovereignty: All audio capture, transcription, and AI summarization are processed locally on your machine, with no data sent to external servers, addressing strict privacy and compliance requirements.
Self-contained desktop application: Meetily is a single application built with a Rust backend and Next.js frontend via Tauri, rather than a cloud service or web app, meaning it must be installed and run directly on a user's desktop.
Flexible AI backend selection: You can choose between running fully local models (Ollama) for total network isolation, or connect to various cloud AI providers like Groq and Claude, or integrate your own OpenAI-compatible endpoint for summaries.
Hardware and GPU acceleration: The application automatically supports GPU acceleration, leveraging Apple Silicon (Metal/CoreML), NVIDIA (CUDA), and AMD/Intel (Vulkan) across supported platforms for improved transcription performance.
Distinct free and commercial versions: The core, open-source Community Edition focuses on local transcription and summarization, while the separate Meetily PRO product adds enhanced accuracy, custom templates, team self-hosting deployment, and advanced exports like PDF and DOCX.
Core Features:
Real-time transcription: Generates a live transcript of the meeting using local Whisper or Parakeet speech-to-text models.
AI-powered summaries: Creates meeting summaries using a choice of AI backend, with Ollama recommended for local, offline processing.
Local-first data storage: Stores all recordings, transcripts, and AI model outputs solely on the user's machine.
Multi-platform audio capture: Captures both microphone input and system audio simultaneously with intelligent ducking and clipping prevention on macOS, Windows, and Linux.
Custom OpenAI endpoint support: Allows configuration of a user’s own OpenAI-compatible API endpoint for generating meeting summaries.
Audio file import: Supports importing existing audio files for post-meeting transcription or re-transcription using different models.
Use Cases:
Professionals handling confidential discussions: Defense consultants, legal professionals, and healthcare providers who cannot risk meeting data being stored on third-party cloud servers can transcribe and summarize sensitive conversations entirely offline.
Developers and technical teams in restricted environments: Teams working in environments with limited or no internet access can use Meetily for meeting documentation, relying on local AI models via Ollama.
Compliance-focused users: Individuals or small groups who need to maintain a clear chain of data custody for meetings, with all processing and storage remaining on-premises on a single machine.
Open-Source Alternative Value:
Meetily provides a practical open-source option for meeting assistance by keeping all data processing on the user's local machine, eliminating the need to send audio or transcripts to external cloud services. Its design allows users to inspect, modify, and build the application from source, and its support for local AI models via Ollama means the tool can function fully offline without any dependency on paid, cloud-based transcription APIs. This creates a verifiable and self-contained workflow for users who prioritize technical transparency and direct control over their meeting data infrastructure.
