Image2PDF – Convert images to PDF online (fast and free)

Hacker News

Hi HN, I built a small tool: [ https://image2pdf.vu ]( https://image2pdf.vu ) It’s a simple image-to-PDF converter, designed to be: - fast (runs directly in the browser), - private (no files are stored on the server), - free. The idea came up when I needed to merge a few photos into a single PDF and most solutions I found were slow, full of ads, or required sign-ups. I’d love some feedback: - How do you find the simplicity of the interface? - What features would you expect (e.g. batch conversion, more image formats, compression)? Thanks!

Visit product View on Hacker NewsAug 26, 2025

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

60%60% 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.

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

45%45% 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

35%35% 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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

9%9% predicted probability of success on Product Hunt, 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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