Get Kevin Hart to summarize your readings

Hacker News

TLDR; demo here:https://youtu.be/1XBU8-AZJRQ Hey guys, recently started getting frustrated with all the readings I was getting at school, since I wasn't learning anything and they took too long. Built a product that lets you paste or upload a picture of any article/text, and have it summarized, broken up into slides and narrated by Kevin Hart. Also includes a text editor for notes, and a dictionary. The goal is to improve a students learning experience from readings, as some are given 50-100 pages of readings per week, which is an insane amount to go through. Would love to get any feedback, or things I could add to improve the product and UX Keep in mind that since this is an early release, there is a lot of things I need to improve for example, the summaries and the voice of Kevin Hart that is generated :) Check out the demo here: https://youtu.be/1XBU8-AZJRQ Try it out here: http://www.smartr-app.life/home If you think its interesting, would appreciate if you could upvote on product hunt: https://www.producthunt.com/posts/smartr

Visit product View on Hacker NewsFeb 4, 2020

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

75%75% 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: notes · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

53%53% 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 · Missing: mobile apps, ios, personal

39%39% 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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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: smart · 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

Similar products

Wordcab, Summarize Every Call42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Wordcab, Summarize Every Call

Hacker News1

Clipped – Summarize Anything42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Clipped – Summarize Anything

Hacker News2

Summarize Any Text46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Summarize Any Text

Hacker News1

Let Me Summarize That for You53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Let Me Summarize That for You

Hacker News6

Summarize and Chat with Any Video32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Summarize and Chat with Any Video

Hacker News2

PodSnacks (Summarize Podcasts with AI)29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

PodSnacks (Summarize Podcasts with AI)

Hacker News1

Summarize Anything, Forget Nothing54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Summarize Anything, Forget Nothing

Hacker News9

Nuggetize30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Summarize any link in seconds

Product Hunt+11

Readzi52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

summarize article in 3 sentences

Indie Hackersai

Summarize links you are about to share44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Summarize links you are about to share

Hacker News1

Browse all products Analyze your launch