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Autocomplete library in JavaScript using trie data structure

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Autocomplete library in JavaScript using trie data structure

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
70%70% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
46%46% 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
36%36% 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
36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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