LandHive AI – The Magical AI Website Engine

Hacker News

Hello HN Today we launched v1 of LandHive AI, an AI driven generator for website which produced website structure, content and design. In this video I showcase the tool - https://youtu.be/0S5rU0odTOk While still an early version, we are already thrilled by the sites that come out of LandHive AI. And we have a lot of ideas to come. Our business model is less of a WIX, SquareSpace competitor but actual enterprise customers who are in need of generating tens and hundreds of sites each year - for example for campaigns, events/conferences, info sites, product experience pages, etc. You can try it yourself today using the prompt form on the website.

Visit product View on Hacker NewsMar 29, 2023

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

71%71% 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: model, using · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal

37%37% 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

31%31% 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

27%27% 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

22%22% 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

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