Shall We Talk

Voice dictation that saves transcriptions on iPhone and Mac

OpenAI DayGitHubProductivity

▲ 62 votes1 commentsLaunched Sep 18, 2026

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Daily #71Weekly #134

Shall We Talk turns speech into clean text on iPhone and Mac. Dictate into any app with a voice keyboard that types at your cursor, Shortcuts, or a Mac hotkey, and record meetings into speaker-labeled transcripts and structured summaries. Cleanup is a proofreader, not a rewriter: it removes fillers and misheard words but keeps your wording, tone and Chinese-English code-switching. Open source (GPL-3.0); bring your own speech and LLM API keys. Advanced from build 200 to 243 with GPT-6 Astra.

AI Analysis

📝 Summary

Shall We Talk is an open-source (GPL-3.0) voice dictation tool for iPhone and Mac that converts speech to clean text. Core features include a voice keyboard for dictating into any app at the cursor, support for Shortcuts and Mac hotkeys, meeting recording with speaker-labeled transcripts, and structured AI summaries. Its Cleanup proofreader removes fillers and misheard words while preserving original wording, tone, and Chinese-English code-switching. Users bring their own speech and LLM API keys for privacy. It solves pain points of inaccurate transcriptions, editing time, and privacy in commercial tools, offering a flexible, accurate productivity solution for bilingual users.

📈 Market Timing

The current market timing is favorable for 2025-2026. Voice AI and LLM technologies have reached high maturity with accessible APIs, aligning with rising demands for efficient, privacy-focused productivity tools amid hybrid work and meeting overload. Growing emphasis on accurate multilingual support and user-controlled AI fits economic pressures for time-saving solutions without heavy subscriptions. Excellent Timing.

✅ Feasibility

Feasibility is High. Technical difficulty is moderate as it integrates existing speech/LLM APIs rather than building from scratch; open-source model enables community support. Development and operation costs are low since users supply API keys. Apple platform compliance is addressed via native integrations with minimal supply chain risks. Scalability is strong through iterative app updates and GitHub contributions, though initial iOS/Mac expertise is needed. High

🎯 Target Market

Main target segments: Tech-savvy professionals and creators using iPhone/Mac (ages 25-50), especially bilingual Chinese-English speakers in Greater China, Hong Kong, and global tech hubs; industries include productivity-focused roles like executives, writers, lawyers handling meetings and notes. Geographic focus: English and Chinese-speaking regions. The dictation and AI transcription market shows strong demand with high willingness to pay for accuracy and privacy (via API costs). Core pains: inaccurate outputs, editing burden, poor bilingual handling.

⚔️ Competition

Medium. Direct competitors: 1. Otter.ai (otter.ai), 2. MacWhisper (macwhisper.com), 3. Descript (descript.com), 4. Fireflies.ai (fireflies.ai). Advantages: Open-source with BYO keys for privacy, unique Cleanup preserving exact tone and code-switching, seamless any-app dictation. Disadvantages: Requires user API setup (less plug-and-play), potentially fewer polished enterprise features or dedicated support compared to commercial alternatives.

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