Cr

Create gamified bite-sized lessons using AI

Hacker News

Create gamified bite-sized lessons using AI

I am a daily user of Duolingo and love the app. Seeing how effective and sticky the app is made me think that teachers should be able to create Duolingo-style lessons easily. Hence, I built this app to help teachers create lessons easily with the help of AI. It's not as comprehensive as Duolingo now but currently has some basic features: 1. Create quizzes with the help of AI. 2. Add/edit questions 3. Publish a quiz. 4. Leaderboards. 5. Scores and analytics for paid accounts. Sharing it here for feedback, and if you know anyone who could use such an app, feel free to share it with them. Thank you!

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% 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
67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
34%34% 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
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · 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: paid · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

I
I Ordered an Uber Using AI44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I Ordered an Uber Using AI

Hacker News1
Us
Using AI to Maximise Holidays31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Using AI to Maximise Holidays

Hacker News4
DialWave
DialWave48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Using AI to revolutionise telephony

Indie Hackers2ai
Gr
GrammarDaily – daily bite-sized grammar lessons44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

GrammarDaily – daily bite-sized grammar lessons

Hacker News16
RenderAI
RenderAI55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Create Images from Sketches using AI

Indie Hackerscommitment-side-project
Growth Lessons
Growth Lessons48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bite-sized lessons from founders of growing businesses

Indie Hackers6mailing-lists
In
IntelliPPT – Create presentations using AI36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

IntelliPPT – Create presentations using AI

Hacker News3
Le
Lessons of HN48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lessons of HN

Hacker News2
Singing lessons Westlake Village
Singing lessons Westlake Village24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Singing lessons Westlake Village

Indie Hackers
Devquest
Devquest34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hands-on learning through interactive and gamified lessons.

Product Hunt+4