FlwKit

FlwKit

TrustMRR

iOS app onboarding development made easy. Launch new flows, analyze and test variants, improve activation without waiting on a new release.

Share card

Actual performance

3customers
$49MRR/mo
Did not reach leaderboard

Traction signals

Domain Rating7
MRR growth 30d+0.6%

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
66%66% predicted probability of success on TrustMRR, 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
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, 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
30%30% 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
29%29% 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
23%23% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

I
I built a new 311 iOS App for SF63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a new 311 iOS App for SF

Hacker News2
Mu
Music for Squirrels – new iOS app36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Music for Squirrels – new iOS app

Hacker News35
Ne
New iOS app to delete similar photos41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

New iOS app to delete similar photos

Hacker News5
Me
Medusa-extender new release 1.6.026%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Medusa-extender new release 1.6.0

Hacker News1
Ne
New Today, My First iOS App40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

New Today, My First iOS App

Hacker News4
be
beanstalk.io our shiny new iOS app for or platform52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

beanstalk.io our shiny new iOS app for or platform

Hacker News1
LASIDO
LASIDO72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

iOS app to improve your sight-reading as a musician

Indie Hackers1$450/moeducation
Ne
New iOS App - Watch your videos from Anywhere36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

New iOS App - Watch your videos from Anywhere

Hacker News17
I
I made an iOS app to analyze and interpret kid's drawings with GPT-439%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made an iOS app to analyze and interpret kid's drawings with GPT-4

Hacker News4
My
My new iOS app showing the Colosseum real-size and scaled20%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My new iOS app showing the Colosseum real-size and scaled

Hacker News3