Presentforme.ai – Make slide decks explain themselves

Hacker News

I noticed slide decks become much less useful after meetings. People send PDFs around, but much of the information was spoken rather than written. I built PresentForMe.ai think of it as DocSend, but interactive. Upload a PDF or PowerPoint and instead of sharing a static deck, viewers get an AI presenter that can: - explain slides - narrate content - answer questions - track all interactions Still working on things like pacing, and making the response more natural. here's a short 3-slide demo: https://presentforme.ai/presenter-live?share=2y_-NRdi0PSyUTW... Would love feedback. Thank you for your attention.

Visit product View on Hacker NewsMay 26, 2026

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Actual performance

2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: plain · Missing: mac, agents, macos

90%90% 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.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

42%42% 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

36%36% 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 · Strong signals: arr, active · Missing: mrr, revenue, profit

18%18% 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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