I made a speech generator for all occasions

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Hey everyone, I am releasing ReadyMadeSpeech https://readymadespeech.com/ , a speech generator, that will generate a speech for every occasion in just a few minutes. There are 600K searches related to wedding speeches and vows in English-speaking countries. Other verticals where I plan to offer speech generation include memorial speeches (170K searches) and special occasion speeches (150K searches). So, I believe it can be useful for many people. To bring this to the market, I had to deal with the hard part: learning how to code. I knew some basic PHP in the 2000s, so I wasn’t starting from scratch, but there was a lot of catching up to do. I am proud that I was able to finish and publish this project after many doubts and problems to overcome. Thanks for the feedback and support!

Visit product View on Hacker NewsJan 27, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% 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.

Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

60%60% 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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos

27%27% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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