DeskSense - Your AI Assistant

AppSumo

DeskSense - Your AI Assistant is highly praised for its user-friendly interface, multiplatform accessibility, and efficient AI capabilities. Some users have expressed minor concerns about delayed customer support and word quota limitations. Overall, with a 4.8 rating and positive feedback, DeskSense is a solid buy, especially with its 60-day money-back guarantee.

Visit product View on AppSumoJun 14, 2023

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Actual performance

31reviews

Did not reach leaderboard

Traction signals

Rating4.7 / 5

Purchases971

Launch Intel predictions

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

76%76% predicted probability of success on AppSumo, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

52%52% predicted probability of success on TrustMRR, 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

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

16%16% predicted probability of success on BetaList, 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.

Incorrect prediction on native model

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