Kobozi

Kobozi

Indie Hackers

Audience Response System

I’m building Kobozi because I believe in creating tools that genuinely help people connect, learn, and grow. An effective audience response system can transform how we engage with each other.

Share card

Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Al
Alaska Bunch – create a poll, pick an audience, collect response data36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Alaska Bunch – create a poll, pick an audience, collect response data

Hacker News4
Co
Code in Response to “The Trouble with Symlinks.”53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Code in Response to “The Trouble with Symlinks.”

Hacker News5
Lo
Lobste.rs for an African audience23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lobste.rs for an African audience

Hacker News3
My
My response to "Why isn't your service free?"72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My response to "Why isn't your service free?"

Hacker News14
Vendorful AI Response Assistant
Vendorful AI Response Assistant29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Cut RFP & infosec questionnaire response time by 90% with AI

Indie Hackerscommitment-full-time
Pr
Predicting Population Migration in Response to Crisis in Yemen27%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Predicting Population Migration in Response to Crisis in Yemen

Hacker News2
Sl
Slashing response time for WordPress29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Slashing response time for WordPress

Hacker News1
In
Incident Response on Steroids56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Incident Response on Steroids

Hacker News1
Se
SetInterval as a Service: Response to Chrome 8837%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SetInterval as a Service: Response to Chrome 88

Hacker News1
Sh
ShiLLM – An LLM that inserts ads into every response39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ShiLLM – An LLM that inserts ads into every response

Hacker News2