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FrequentlyAskedAI – An interactive AI FAQ alternative to chatbots

Hacker News

FrequentlyAskedAI – An interactive AI FAQ alternative to chatbots

I originally released an interactive resume tool and that went well but I got pulled in another direction by HN. HN really slammed my server on the original thing I built (thanks for the unexpected but useful battle testing, I learned a lot). More importantly some people reached out and said they wanted to use it for their business, not professional networking, which led me down a completely different path for a different tool using similar tech. Long story short, these businesses: 1) Wanted to know more about what their customers wanted but couldn't necessarily rely on customers reaching out to them 2) Spent more time answering similar questions than they'd like 3) REALLY hated chatbots and didn't want to pay for/train customer service agents yet I added a bunch of features they asked for like being able to embed my tool on their website, customize the quick questions, and add related links that can route their customers to other URLs. That last feature request was particularly interesting. Two businesses independently asked for this and they used it to basically make a mini Google search for their complex product (e.g. to direct customers to the right help pages, tutorials, etc). I have no idea where this project is going to end up yet and it's already turned in a direction I didn't expect. I'd love y'all's thoughts on the latest. Here's a link to my new home page with more information: https://www.infaq.ai Forgive me for lack of visual elements and some of the corny marketing text. Many are placeholders and I'm working on it. Also shout out to the business owner that went out of their way to find me this relevant domain name. We were joking that my tool should actually be called InfrequentlyAskedAI since it actually handles a long tail of questions.

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Actual performance

2points
4comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, google · Missing: mac, macos, cursor
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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