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Free Transactional Email Plans – Live, Scraped Limits

Hacker News

Free Transactional Email Plans – Live, Scraped Limits

Working for a non-profit, I need to use as many free services as possible. Emails are part of it. Free tiers often change, hence this small tool. I built it with Claude 4.5 (approximately 10 hours of work) with barely any coding experience. It generates daily a lightweight comparison of transactional email providers that only lists services with a renewable free tier, showing daily/monthly limits from live scrapes and clearly marking static fallbacks. What do you think? Did I miss any providers that meet the "renewable free tier" criteria?

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: month, monthly · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
50%50% predicted probability of success on Indie Hackers, 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: claude, new, email · Missing: mac, agents, macos
28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: profit · 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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