I

I Built an AI to Do Customer Interviews for Shy PMs and Hackers

Hacker News

I Built an AI to Do Customer Interviews for Shy PMs and Hackers

A few months ago, I left my job as a PMM to build my own startup before I turn 30. The problem? Customer feedback surveys and interviews suck. Most businesses rely on email or in-app forms, but response rates are low, and insights are shallow. So I built something different: an AI-powered calling agent that conducts real-time, human-like voice interviews. It doesn’t just collect feedback the software analyzes every conversation and gives you actionable insights on what to add to your product and what to improve. No more ignored surveys—just real customer conversations at scale.

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: agent, email · Missing: mac, agents, macos
93%93% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, 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
44%44% predicted probability of success on Hacker News, 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
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
24%24% 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

Aptitude
Aptitude71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Customer interviews, conducted and analyzed by AI

Product Hunt+243Design Tools
th
the LIMITLESS pill for hackers58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

the LIMITLESS pill for hackers

Hacker News1
Ha
Hackercouch - couchsurfing for hackers58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hackercouch - couchsurfing for hackers

Hacker News2
Ha
Hackerforms Is Typeform for Hackers58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hackerforms Is Typeform for Hackers

Hacker News11
An
Any salsa dancer hackers here?58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Any salsa dancer hackers here?

Hacker News2
An
Any salsa dancing hackers here?58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Any salsa dancing hackers here?

Hacker News2
Ma
March Madness for Hackers60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

March Madness for Hackers

Hacker News100
Customer Discovery Sprints
Customer Discovery Sprints41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Done-for-you customer interviews.

Indie Hackerscommitment-side-project
Customer Discovery Sprints
Customer Discovery Sprints61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Done for you customer interviews.

Indie Hackerscommitment-side-project
Bo
Bored Hackers – A public chatroom for hackers57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bored Hackers – A public chatroom for hackers

Hacker News14