Causabi, a tool to create interactive, HTML-based product demos

Hacker News

The problem came straight from my own experience: I lost leads because my demos took too long to create, often broke, or simply weren’t personalized enough. I was always trying to juggle two things at once — maintaining and building demos, testing them, and improving the product — and in the end, I never had enough time for either. I wanted something that felt just like the real product but was quick to build from my existing work and easy to customize. That’s why I created this tool — made specifically for SaaS and AI founders (and sales teams). The goal is simple: personalized demos without coding, without bugs or headaches, and absolutely no screenshots or videos. With Causabi, you can: - Capture your UI via a Chrome extension - Add tooltips, highlights, modals, and walkthroughs - Personalize with variables (e.g. {{first_name}}) - Generate multiple demos from templates or CSVs - Track demo analytics to optimize performance Everything runs in the browser and the end result feels like a real product — not a slideshow or video. It’s still an early version (a bit rough in places), but it’s already usable, and I’d love your feedback. here you can try a demo - https://www.causabi.com/ (from pc) here you can made your own demo - demo.causabi.com

Visit product View on Hacker NewsMay 27, 2025

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

95%95% 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: created · Missing: supports, reddit linkedin, podcasting

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

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

36%36% 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, 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 · 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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