Fetch

Fetch

Indie Hackers

Cross SaaS search made easy with Fetch

Working as a Software developer in different companies and environments, we realized that a very simple use case of finding what we want was cumbersome. Fetch is an attempt at fixing this!

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Actual performance

3followers
Made the leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
55%55% predicted probability of success on Indie Hackers, 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
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
38%38% 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
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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
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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