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VectisPDF – Fast, private in-browser PDF suite (No uploads, Rust/WASM)
VectisPDF – Fast, private in-browser PDF suite (No uploads, Rust/WASM)
Share cardActual performance
3points
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Launch Intel predictions
Analyze your own launch →57%57% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
25%25% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
16%16% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Correct prediction on native model
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