Superpowered (YC W21) – The AI copilot for your meetings

Hacker News

Hey y’all, I’m Nikhil from Superpowered ( https://superpowered.me ), here with my cofounders Jordan and Ibrahim. We’re launching an AI tool that we’ve built. We got destroyed last time we launched on HN over 2 years ago. https://news.ycombinator.com/item?id=26425318 . We went through many product pivots since then and things got weird. At one point, we tried to train a neural net to predict the next app you'll use, lol. But, we’re a lot happier where we find ourselves now: AI copilot for your meetings. We don’t send any bots to your meetings, we don’t keep any recordings, we just give you really good notes. Check out https://superpowered.me . You’re likely thinking of your next savage comment. “Here comes another thin wrapper over OpenAI”. And, you’re likely funny and correct. But, before you dismiss us, please consider what we're hearing from our users: - “What can I say—I'm amazed! I've only really been using the notes today and I'm stunned by how helpful they are. I legit ran downstairs to show my wife what Superpowered is able to do. She's going to sign up now!” - “AI notes in Superpowered are the best thing to come out of AI thus far.” Anyways, don't knock it until you try it. Thanks. Looking forward to hearing your thoughts. Nikhil P.S. Jordan recorded a great video of our journey. There is an abbreviated version on Product Hunt. But, here's the full version for y'all: https://youtu.be/Zo16RzvtiKk P.P.S We're live on PH: https://www.producthunt.com/posts/superpowered-3 . Would appreciate any support.

Visit product View on Hacker NewsJun 14, 2023

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

90%90% 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, new, recordings · Missing: mac, agents, macos

81%81% 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

66%66% 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: video, users, way · Missing: mobile apps, ios, personal

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

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% 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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