Dunlo

Dunlo

TrustMRR

Stripe payment recovery for SaaS founders. Reads the failure reason before sending anything — expired card, insufficient funds, and donothonor get different emails, timing, and escalation paths. No re

Stripe payment recovery for SaaS founders. Reads the failure reason before sending anything — expired card, insufficient funds, and donothonor get different emails, timing, and escalation paths. No recovered-revenue cut. Free until July 31, 2026.

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating1

Launch Intel predictions

Analyze your own launch →
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: stripe, email · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, saas · Missing: arr, mrr, profit
28%28% 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
26%26% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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