Wispr Flow?

YESA focused first version is a sensible AI-assisted build. Keep the first release narrow and polish the workflow people repeat.

BUILD FIRST

One defined user and a repeatable end-to-end job
A small, clear data model with sign-in only if it is genuinely needed
Loading, empty, error, and success states that make the workflow feel complete

LEAVE FOR LATER

Large integration marketplaces
Multi-region scale and enterprise administration
Every power-user setting from the established product

RESEARCH NOTES

What this tool actually does.

Checked 2026-09-06

Wispr Flow is voice-to-text software for Mac, Windows, iPhone, and Android that turns natural speech into polished writing wherever the user can type. Its public product pages describe global dictation, filler removal, punctuation and formatting, vocabulary and snippets, app-aware style, and settings that control cloud transcription, context awareness, storage, and model-improvement data.

SOURCES

RESEARCHED BUILD PROMPT

Give this to your coding agent.

Build a focused desktop dictation utility for knowledge workers. Do not copy Wispr Flow's brand, proprietary assets, or UI.

Core workflow
- Target Mac and Windows first. Add a configurable global hotkey with hold-to-talk and toggle modes, microphone permission onboarding, recording state, cancellation, and a clear permission/error path.
- Send captured audio to a transcription provider and show an editable transcript. Add a cleanup pass for filler words, punctuation, paragraphs, spoken corrections, and simple formatting, then insert the resulting text at the active cursor through an accessibility/clipboard bridge.
- Use provider adapters so the user can choose a hosted API model or a local Whisper-compatible model. Put provider/API key, language, hotkey, microphone, active-app context, history retention, and privacy controls in Settings.
- Add a local dictation history and optional custom dictionary/snippets, with an explicit toggle for storing audio/transcripts and for sending surrounding textbox context. Explain that cloud transcription is not local-only.

Implementation and scope
- Use Electron or Tauri with a small local store and native global-shortcut/accessibility bridges. Start with a tested set of desktop targets and show when an app cannot accept insertion.
- Out of scope: mobile clients, meeting recording, team administration, 100+ language parity, enterprise certification, and claims of universal app compatibility.
- Include seeded transcript examples so the cleanup and insertion flow is testable without a microphone.

Include a README with setup, OS permissions, model/provider configuration, privacy choices, and important limitations.

Visit the official product page