Free In-Browser .msg Viewer

Hacker News

On my job I needed to see the content of Outlook .msg file. You might assume that, I could simply open it in Outlook app. It might have worked on Windows, but not on Mac. As there it expects .eml instead of .msg. I also didn't want to use any website that in order to parse the file uploads it to an external server. It is insecure and violates the company policy as the internal data can be exposed. So, I decided to create a simple .msg viewer that doesn't send any request to an external server and reads the file in browser. It is extremely fast and safe as the data is not shared with third parties.

Visit product View on Hacker NewsSep 29, 2024

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, open · Missing: agents, macos, agent

72%72% 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

56%56% predicted probability of success on Indie Hackers, 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

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

38%38% 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

34%34% 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

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

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

Incorrect prediction on native model

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