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I built a service to detect invalid and malicious email addresses

Hacker News

I built a service to detect invalid and malicious email addresses

Hello HN, around October last year, I started to work on campaignkit.cc as a side project. It is a service to detect invalid and malicious email addresses. You can upload text files, and use the REST API or direct integration to retrieve a detailed report for each email address. End of March I added Stripe Payments and got my first paying customers via SEM. A coworker suggested starting a Show HN thread, so here we are :) I used golang for the backend since I wanted something lightweight with fast compilation times (coming from scala). For the frontend, I'm using Next.js and TailwindUI. On the further roadmap, I plan to provide more services around email deliverability. This includes Inbox placement, Backlist monitors and DMARC Analyzer. I’m happy to answer questions, take criticism, and generally hear what you think.

Visit productView on Hacker NewsApr 21, 2022
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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: stripe, inbox, email · Missing: mac, agents, macos
86%86% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
48%48% 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
45%45% 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
40%40% predicted probability of success on AppSumo, 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
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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