A Secure Form Autofill Easy to Use

Hacker News

Hi HN, I got tired of repeatedly filling out the same web forms and noticed that the main existing tool have moved to subscription models. So, I built an alternative that securely saves your form data and automatically fills it the next time you visit the same page. Features: -Secure Encryption: Uses AES-256 encryption to store your data locally—nothing is sent to external servers. -Works on all input types (checkbox, color, date, email, hidden, number, radio, range, search, text, time), textarea fields, select/option fields and content editable elements. -Multiple Profiles: Create different profiles for work, personal use, or any other context. Hope it is helpful as it was for me. Would love your feedback pls

Visit product View on Hacker NewsOct 17, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, email · Missing: mac, agents, macos

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% 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: personal · Missing: mobile apps, ios, entrepreneurs

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

14%14% 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.

Correct prediction on native model

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