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Phixo – AI Phishing Protection for Gmail and Outlook

Hacker News

Phixo – AI Phishing Protection for Gmail and Outlook

Hi, I am a Solo developer and I have created a Chrome extension to help prevent email phishing in Gmail and Outlook. This extension tells you why an email has phishing signs and also blocks the phishing URL if it finds something suspicious. I am posting here to get feedback so I can improve my extension further. Although it's still in the early stages, I am improving it with time. If you guys could check it and give me any feedback, that would be very helpful for me. Anything good or bad is welcome. I would also like to hear your thoughts about the idea of creating a phishing protection extension for Outlook and Gmail. Website: https://phixo.app/ Chrome Extension: https://chromewebstore.google.com/detail/diakennfllmgdpepggh... Demo Video: https://youtu.be/cWbeWcAqpzc?si=sE5eWfFvWPpFQLG2

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
55%55% 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 HuntUnlikely to reach the leaderboard · Strong signals: google, email · Missing: mac, agents, macos
48%48% 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
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, google · Missing: mobile apps, ios, personal
39%39% 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, io · Missing: https docs, excited, just released
22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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