A no-watermark video downloader for Any social media

Hacker News

Hi HN reader, I'm a solo-founder navigating product market fit. I've spent 3 years building Double Subtitles which I am very proud of, but I don't know how to do marketing and my growth is somewhat stagnant. Through learning about SEO, I discovered this opportunity that I want to share: There are a lot of websites that let you download social media videos, which have extremely high traffic. But they are all disjoint, in the sense that some download TikTok videos, while others download Instagram videos, others YouTube, etc... I quickly prototyped software which downloads any video from any link. Currently the live version of FastDownload only supports TikTok and YouTube videos, since they are the most stable. But I will slowly start rolling out Instagram and other services weekly. ps. Personally, what I think is really cool is this Apple Shortcut, which lets you download videos directly from within whatever app you're in, using Share Action Extensions. pps. Another thing I'm very excited about is that while doing analysis with Ahrefs and SEMRush I have been able to identify many high value keywords which I'm deploying pSEO strategies for now. I hope this product is helpful and any feedback (even negative) would bring me joy. All the best, Bojan

Visit product View on Hacker NewsApr 17, 2024

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

95%95% 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 HuntOn track for Day 1 leaderboard · Strong signals: apple, using · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, video · Missing: mobile apps, ios, entrepreneurs

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% 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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