Pouces – input method for iPhone

Hacker News

Pouces combines taps and swipes to allow fast text entry and its six regions enable to input text without looking at the input window but rather the text being written. Current features include: • Fast access to numbers • Support accented characters • Quick input for capital letters • Text replacement • Quick delete I would like to get some feedback on usability and/or features from anyone willing to try it out, here are some promo codes: 1 YAW47JNEEETR 2 L96MNJ4RHN6Y 3 3PHP3MYM3HEL 4 66NNKA4AHHMY 5 6W43JFTE44N4 6 3L9JW4THRKTT 7 A9JKJE3F4A6N 8 3REJYPWLPXYE 9 J9Y6AEHM6436 10 3KRKT6RTM6KY 11 EX3YTAFRLHWP 12 4KFX93A73X4J 13 XMLKAF66WLLM 14 9ALX6XETFMH6 15 AEHM7RJTEA6K app store ($1.99) link : http://itunes.com/app/pouces

Visit product View on Hacker NewsJun 18, 2016

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos

39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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