Offline transcription and summary tool

Fully offline meeting transcription, diarization, and summarization for privacy-conscious users

Problem

Many meeting and interview transcription tools rely on the cloud, posing privacy risks and charging high per-minute fees. Users need to process sensitive audio locally, but existing open-source solutions are complex to set up or lack diarization and summarization.

Solution

Build an offline desktop app that uses local Whisper models for transcription, integrates speaker diarization (e.g., pyannote) and local LLM-based summarization. All data stays on-device, with a clean UI and export to timestamped text and Markdown summaries.

Users

Journalists, lawyers, researchers, corporate legal teams handling sensitive audio

MVP

Import audio files; local Whisper transcription with timestamps; simple speaker diarization via voice clustering; local summarization; export to txt/md

Revenue

One-time purchase ($49) or annual subscription ($29/year), enterprise bulk licensing

Why now

Tightening privacy regulations and mature local AI models; indie developers can build on open-source models without cloud costs