SaasRock KB – Open-Source Knowledge Base Builder with Wysiwyg Support

Hacker News

Open-sourced SaasRock KB! A Knowledge Base starter kit built with Remix, Tailwind CSS, and Prisma. All features - Intercom/Crisp-like knowledge base structure - WYSIWYG editor with @tiptap_editor - Markdown editor - Multi-knowlege-base support - Multi-language support - Simple Analytics: Track Views and Votes - Image Storage with @Supabase - Article Duplication: Don't write from scratch - Article Drafts: draft and published copies - Import and Export: Quickly transfer knowledge bases - SEO meta tags Watch the introduction demo: https://www.loom.com/share/c5d6a04da4214e3689b38d0e5d211e25

Visit product View on Hacker NewsJun 29, 2023

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

18%18% 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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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