Factiverse AI editor – Fact-checking text made smarter and simpler

Hacker News

Heya HN, after 7 years of dedicated work, we're thrilled to unveil Factiverse AI Editor - a revolutionary tool to validate or debunk factual claims in any text, including AI-generated content. Here's how it works: Our cutting-edge machine learning models analyze your text and identify check-worthy claims. We then scour search engines like Google, Bing, and Wikipedia, alongside manual fact-checks, to retrieve supporting and disputing evidence. The credibility of each source is carefully assessed using another machine learning model trained on expert fact-checks. Try out the Factiverse AI Editor at https://editor.factiverse.ai/ and be sure to sign up and provide feedback on our Product Hunt page at https://www.producthunt.com/posts/factiverse-ai-editor or directly within the app. To get started, check out our tutorial video at https://youtu.be/rMBHHfn6mk0 and hear a special message from the founders at https://youtu.be/Ri5rR_clpxg . Visit our homepage at http://factiverse.ai for more information. Join us in revolutionizing fact-checking with AI!

Visit product View on Hacker NewsJun 23, 2023

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Actual performance

65points

28comments

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, google · Missing: agents, macos, agent

79%79% 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 · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, google · Missing: mobile apps, ios, personal

53%53% 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, including · Missing: https docs, excited, just released

45%45% 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

34%34% 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

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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