Typosaur, the interactive spell-checker for modern web

Hacker News

Hello, I'd like to showcase a project I've been working for some time now The project is called Typosaur and is an interactive spell-checker that provides spelling, grammar and style suggestions Typosaur is a great fit for Blogs, Documentation and Marketing sites and also supports Single-Page-Apps Typosaur is currently in Beta and I'd love to hear your feedback! The API is also available in preview, shoot an e-mail hello@typosaur.com if you want to get access! --- My goal is to free the web from embarrassing spelling mistakes and improve writing without the need of dedicated writing teams. If you think you can help us achieve this goal (financially or with your talent), I'd love to hear more from you! Thanks for your attention!

Visit product View on Hacker NewsJun 18, 2022

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Actual performance

3points

Did not reach leaderboard

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

88%88% 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: apps, single · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr, active · Missing: mrr, revenue, profit

11%11% 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

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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