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Instorier – story-first website builder. No-code, AI-optional

Hacker News

Instorier – story-first website builder. No-code, AI-optional

We're two founders from Tromsø, Norway who have spent the past 4,5 years bootstrapping Instorier. Everything you see here, from the editor to the runtime, we built from scratch. Instorier is a modern website builder focused on storytelling. Out of the box it supports 3D/WebGL scenes, map journeys, and motion, with real-time collaboration and instant hosting. You can also embed Instorier stories into an existing site without a migration. What's new now: an AI-optional onboarding flow. It helps you get started quickly, but keeps authorship yours. This isn't about generating cookie-cutter sites, it's about lowering the barrier to telling meaningful stories online. We've found some early product-market fit in the media industry, like with Stavanger Aftenblad in Norway and Scrolli.co in Türkiye. At the same time, broader adoption has been harder. That's why we're now also exploring use cases for startups, comms teams, and agencies, while keeping the focus on what we believe makes any landing page or article succeed: engaging, meaningful storytelling. Tech stack is Next.js and React for the service, React, Redux Toolkit, Three.js and lots of other custom JS/TS for the Editor, and the website runtime is very custom and uses Three.js for some heavy lifting. Also we've disabled scrolljacking by default since posting here last time :)

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created
88%88% 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: new, code · Missing: mac, agents, macos
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: exist, existing, io · Missing: https docs, excited, just released
44%44% 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 · Strong signals: host, builder · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
15%15% 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
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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