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Whize (Alpha) – Discovery focused search engine

Hacker News

Whize (Alpha) – Discovery focused search engine

https://alpha.whize.co Hi there, so this is an early version of Whize, a discovery focused search engine. Currently, as a proof of concept / concept demo we've crawled all (as of a few weeks ago) of public github and given you a search engine that returns repo results based on relevancy and our notion of novelty and recency. We are privacy focused and want to provide a search experience that doesn't follow you across the internet. We would love feedback and generally, we are trying to figure out if we should expand on this and are trying to gauge people's interest. You can read in-depth about what we are trying to do here: https://medium.com/@iantbutler01/existing-search-engines-fail-independent-and-small-businesses-enter-whize-404958949534

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
64%64% 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.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% 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
23%23% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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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