Mai Tai – Turn your documents into a live Q&A

Hacker News

Hi everyone! I put together a small web application which lets you upload documents and gives you an AI chatbot that answers any questions you may have. I built the site because my developer colleagues and I spend way too much time searching through API documents looking for answers to our questions. I figured that it'd be nice to have an assistant to do the reading for us. Friends of mine have also found it helpful as a study buddy, getting answers from documents in other languages, and finding specific excerpts in long documents. I have no idea if this would be helpful for anyone else, but I'd love to hear the community's feedback. And if it's totally useless I'd be interested to hear that as well. Thanks!

Visit product View on Hacker NewsApr 19, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

73%73% 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 · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: answers, way · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, 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

43%43% 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

42%42% 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

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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