Flagup

TrustMRR

FlagUp is a customer support and feedback platform for SaaS teams. Its AI Support Agent answers customer questions using your Knowledge Base and connected APIs, while the same widget collects feedback, suggestions, bugs, and feature requests. FlagUp also analyzes sentiment, detects duplicates, prioritizes requests, and brings everything together in one dashboard with roadmaps, changelogs, and product insights.

Visit product View on TrustMRRFeb 1, 2026Artificial Intelligence Other B2B

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Actual performance

1customers

$19MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating1

Launch Intel predictions

Analyze your own launch →

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

88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Hacker NewsMay not resonate with HN audience · Strong signals: 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.

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

35%35% predicted probability of success on BetaList, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

27%27% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

27%27% 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

21%21% 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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