Si

Single Sign-On application with complete security and privacy

Hacker News

Single Sign-On application with complete security and privacy

We at www.smartsignin.com has developed a Single Sign-On system which gives your complete security and privacy by letting you choose your own decryption key (Cryptphrase) which makes you the sole owner of your data. We use client side encryption/decryption and doesn't store user's cryptphrase on the server thereby ensuring that not even the employees of SmartSignin can ever access user's data.<p>We have made it possible by using out patent-pending SmartKey algorithm developed in joint venture with Ganita Labs, University of Toronto.<p>Would love for HN people to try it and provide some feedback.

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Actual performance

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
72%72% 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: user, single, using · Missing: mac, agents, macos
67%67% 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
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
34%34% 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 · Missing: mobile apps, ios, personal
33%33% 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
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · 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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