I'm 13 and built an AI that remembers context across conversations

Hacker News

Hi HN! I'm Amber (13) and my dad Raj, and we built Nityasha AI from Guna, India. After my dad's 12 years of failed startups (2012-2023), we created a personal AI assistant that handles email, coding help, research, and planning in one conversational interface. I started coding at 9 on a 4GB RAM laptop. We failed 8 times before this—coupon sites, freelancing platforms, consulting. Nityasha is different: it uses Thesys generative UI for visual charts, includes Study Mode with Socratic teaching, and integrates everything so you don't need 10 tabs open. 500+ active users now. We just launched Nityasha Connect where businesses can integrate services directly into the AI. Would love your feedback!

Visit product View on Hacker NewsOct 22, 2025

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

88%88% 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, started · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, interface, users · Missing: plus, intuitive, reviews

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

53%53% predicted probability of success on TrustMRR, 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

49%49% 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 · Strong signals: active · Missing: arr, mrr, revenue

18%18% 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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