Cleanlist AI

AppSumo

'Customers are all about Cleanlist AI, praising its exceptional data quality, 15+ provider data waterfall, and accurate verification. There are a few hiccups like minor glitches and limitations in usage, just small bumps on the road. Weighing the raves against the occasional grumbles, Cleanlist AI is hitting the mark and is a solid buy at $79.00, especially with the 60-day money-back guarantee.'

Visit product View on AppSumoJul 31, 2026

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Actual performance

114reviews

Made the leaderboard

Traction signals

Rating4.8 / 5

Purchases1,052

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.

AppSumoStrong fit for a featured deal · Strong signals: occasional · Missing: plus, platform, intuitive

59%59% predicted probability of success on AppSumo, 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

43%43% 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

37%37% 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: ide, io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

19%19% 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

14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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