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Launching an AI search engine for Czechia

Hacker News

Launching an AI search engine for Czechia

We are launching an AI powered search engine for the Czech market. We are launching an AI powered search engine for the Czech market. We are launching an AI powered search engine for the Czech market. Our search engine leverages intelligent agents to explore both the web and its own dynamically built internal database, created as it crawls sites. We believe this approach delivers more meaningful results, bypassing the clutter of sponsored content and SEO-gamed pages that dominate traditional search rankings.

Visit product View on Hacker NewsOct 21, 2024

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

65%65% 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.

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

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

43%43% 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

40%40% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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