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Wispr Flow – A new voice dictation experience

Hacker News

Wispr Flow – A new voice dictation experience

Hey HN! We're Tanay and Sahaj from the Wispr Flow team ( https://flowvoice.ai ). Today, we're officially launching Flow: a Mac dictation app that lets you speak naturally and writes in your style, in every application — with auto-edits, command mode, and over 100 languages. Watch a quick 90 second demo here (feat. Steve Wozniak): https://www.loom.com/share/2fd33f10407947b08c6d688398d8679e PS: Last week, Rahul Vohra from Superhuman called it "the best AI product I've used since ChatGPT ", and hearing it honestly made my day. [The founding story] Ever since I watched the first Ironman movie in 2008 at age 10, I've wanted to build Jarvis. It drove me to pull my first all-nighter and teach myself code. 16 years later, we've found a way to make a voice experience delightful for all-day use. And there's no one else I'd build this with than my college roommate and closest friend, Sahaj. Our vision is to make voice interfaces useful (so you trust them) and ubiquitous (so you can use them everywhere). This is how we can move from screen-first to voice-first technologies and build a future where we aren't stuck looking at our phones all day. [Using Flow is super simple] - Download Flow for Mac (Apple Silicon only - others coming soon) - Press and hold [Fn] to start speaking in any app - Release [Fn] to enter text [What users love Flow for] - Developers using Cursor / Claude / ChatGPT: Speak with AI assistants faster than typing. - Professionals breezing through their inbox: Flow accurately captures names and formats your emails and Slack messages. - Students chatting with AI and finishing assignments even faster: We have a special student discount. - Product Managers drafting PRDs and sharing thoughts: Flow turns your rambles into clear ideas. - Parents with busy lives: Time is precious. Every second you save writing is an extra second you have for family. - Tech-lovers who want to use voice with every AI tool What makes Flow different is we designed our models for zero-edit messages - the metric that users really care about, instead of 'word error rates'. For comparison, Apple / Google dictation is <5% zero-edit messages (i.e., 95% of the messages, you have to correct at least one word). Flow today is 50-70% of the messages being zero-edit, based on the use case. After six months of sleepless nights with our team, we had our first set of users who organically started using Flow more than their keyboards. Today, that's a large fraction of our users. Still, we have a long way to go, and we're just getting started. Would love for you to try it out at https://flowvoice.ai (web playground and desktop app). You can keep using the free version (2000 word / week limit) or upgrade to the Pro version starting at $12 / mo (annually). For the HN community, use the HNLAUNCH promo to get 33% off (or 4 months free on the annual plan) PS: A massive shoutout to our thousands of beta users who've showered us with love and feedback over the last few months. We wouldn't be here without you. Our dream is to create a world where interacting with technology feels as natural as interacting with people. I'd love your help to make this a reality. We’d love to hear your ideas and comments with voice intelligence! Bonus points if you write your comment with Flow ;)

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
98%98% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, cursor, claude · Missing: agents, macos, agent
97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: month, google, users · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, soon, users · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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