Frank AI

AppSumo

'Customers appreciate Frank AI for its impressive performance, seamless iOS and web integration, and the ability to use the latest AI models on the go. While some users have noted minor drawbacks such as limited language support and interface issues, the overall sentiment is positive. With an impressive 4.5 rating and 140,000+ users from over 100+ countries, Frank AI seems to be hitting the mark and is a solid buy for those in need of a powerful AI assistant. Plus, with a 60-day money-back guarantee, it's worth giving it a try.'

Visit product View on AppSumoJul 8, 2024

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Actual performance

44reviews

Did not reach leaderboard

Traction signals

Rating3.1 / 5

Purchases630

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: plus, interface, users · Missing: platform, intuitive, reviews

91%91% predicted probability of success on AppSumo, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, models · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, users · Missing: mobile apps, personal, entrepreneurs

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released

38%38% 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

27%27% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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