Mindstamp – Make Any Video Interactive

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Hey HN! My name is Brett and I'm the solo developer behind Mindstamp. Mindstamp turns any video into a two-way, interactive experience by layering in clickable buttons, hotspots, quiz questions, branching, images, and a whole lot more. Here's a quick walkthrough: https://youtu.be/CD42oKQjnKI Back in 2018, I built a product called Aech that let you add comments on top of videos for your friends so it felt like you were watching together. That didn't quite work, but it got into the hands of a couple video agencies using it for client feedback, and for the past 7 years I've listened to the feedback that users have given to continually improve the platform. Today, we are used primarily by corporate training teams and educational institutions that want to ensure their content is being 1. watched and 2. understood. Rather than watching a video and taking a quiz at the end, we put that quiz right inside the video to ensure they are paying attention. Here's a live demo: https://mindstamp.com/demo Mindstamp is built using a Rails backend and a Vue.js frontend. A few months back, I completed a full rebuild of the entire app since it accumulated a lot of technical debt after 7 years of learning while building. It took me 12 months, but now I can sleep at night, so I'd say it was worth it. Happy to answer any questions or provide more info. Thank you!

Visit product View on Hacker NewsOct 28, 2025

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

92%92% 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: user, using · Missing: mac, agents, macos

91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

51%51% 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

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.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% 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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